The DOI matches its Crossref record; 62 of the 63 references it cites were found in a registry or an index, and 1 are not checked yet; 7 of the 54 sources its claims cite were checked for support.
Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization
Open accessAbstract
This study examines algorithm effects on user opinion, utilizing a real-world recommender algorithm of a highly popular video-sharing platform, YouTube. We experimentally manipulate user search/watch history by our custom programming. A controlled laboratory experiment is then conducted to examine whether exposure to algorithmically recommended content reinforces and polarizes political opinions. Results suggest that political self-reinforcement, as indicated by the political emotion-ideology alignment, and affective polarization are heightened by political videos – selected by the YouTube recommender algorithm – based on participants’ own search preferences. Suggestions for how to reduce algorithm-induced political polarization and implications of algorithmic personalization for democracy are discussed.
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Claims the paper makes
33 Own interpretation · 19 No full text of the sources · 12 Own result · 10 Own method · 5 Partly supported · 4 Not checked yet · 3 Sources not found · 2 Supported so far · 2 No basis given · accuracy not yet measured
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Existing evidence suggests that the pattern of individuals' information seeking and consumption is more nuanced and multifaceted than assumed in the notion of selective exposure and homophily.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
What the sources say
- Not checked — no full text of the sourcecites Beam, 2014 source
- Not checked — no full text of the sourcecites Garrett et al., 2013 source
- Partly supportedcites Hart et al., 2009 sourceExperimental — accuracy not yet measured
The Results (page unavailable) show that information selection depends on utility: participants sometimes favored information that challenged their existing views. This supports a more nuanced account of selective exposure, but the paper does not assess homophily, so that part of the comparison is unsupported. (LLM, conf=0.82)
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Results suggest that political self-reinforcement, as indicated by the political emotion-ideology alignment, and affective polarization are heightened by political videosselected by the YouTube recommender algorithmbased on participants' own search preferences.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Abstract
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Results suggest that political self-reinforcement, as indicated by the political emotion-ideology alignment, and affective polarization are heightened by political videosselected by the YouTube recommender algorithmbased on participants' own search preferences.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Abstract
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As shown in the results, ideas perceived to be discussed in one's social circles, if adopted as search terms by the user, weaken reinforcing effects of algorithms.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This pattern is particularly pronounced for negative emotions such as anger and sadness.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Ideological Reinforcement
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results suggest that there were no significant differences in affective polarization across the three conditions (i.e., self, social, and control), especially when it came to specific discrete emotions (i.e., anger, fear, sadness, joy, and hope) (see Table 2).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Affective Polarization
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of these, the difference between the social condition and the control condition for sadness turned out to be statistically significant, based on z-statistics.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Ideological Reinforcement
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“the negative correlation across all conditions indicates, not surprisingly, that participants who identified themselves as liberal tend to feel less anger toward Clinton than toward Trump.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Ideological Reinforcement
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In contrast, such a pattern of reinforcement and polarization was less salient when algorithms were fed with socially generated search terms.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the results of our study suggest that the reinforcing effects of algorithms diminish as users employ search terms cued by social networks”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Conclusion
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 24
- Probably not a substantial claim. 40
- The quote only partly states this claim. 2
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Although people do not necessarily avoid attitude-discrepant messages (Ahn et al., 2014;Beam, 2014;Garrett et al., 2013), it is more likely that attitude-consistent messages that resonate with them and confirm their desired conclusions are preferred (Feldman et al., 2018;Gentzkow & Shapiro, 2011;Stroud, 2011).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Algorithmic Personalization
What the sources say
- Not checked — no full text of the sourcecites Feldman et al., 2018 source
- Partly supportedcites Gentzkow & Shapiro, 2011 sourceExperimental — accuracy not yet measured
The Introduction reports that conservatives and liberals have somewhat different ideological exposure in their online news diets, consistent with some selection of attitude-consistent outlets. But Section 6 says the study cannot directly observe which stories people choose within those outlets, and the Introduction says its evidence does not address how people translate content into beliefs. It therefore does not establish that messages are preferred because they resonate with readers or confirm desired conclusions. (LLM, conf=0.85)
- Not checked — no full text of the sourcecites Stroud, 2011 source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Recommender algorithms installed on online platforms help users efficiently access the information they are looking for while also reducing information overload (Hannak et al., 2013;Lazer, 2015).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Algorithmic Personalization
What the sources say
- Partly supportedcites Hannak et al., 2013 sourceExperimental — accuracy not yet measured
The Introduction describes personalized search as ranking webpages a user is likely to be interested in more highly, which supports the information-finding part of the claim in principle. But the Recommendations section says the study did not determine whether personalization improved users’ search experiences, and the passages do not establish that it reduces information overload. (LLM, conf=0.83)
- Not checked — no full text of the sourcecites Lazer, 2015 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Partly supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“Based on some kind of input, recommender systems select a set of items from a large pool of available items and recommend a list of information links for users to choose (Resnick & Varian, 1997).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Algorithmic Personalization
What the sources say
- Partly supportedcites Resnick & Varian, 1997 sourceExperimental — accuracy not yet measured
The Recommender Systems section says systems take recommendations as inputs, aggregate them, and direct them to recipients; it also describes recommending interesting items. But it does not characterize recommender systems generally as selecting from a large pool and presenting users with a list of information links. It describes links as one possible type of recommendation alongside books, movies, and other items. (LLM, conf=0.84)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“It is proposed that there are two distinct but coexisting human motivations that account for citizens' choice and consumption of political information: directional vs. accuracy (Kunda, 1990, or defensive vs. accuracy in Hart et al., 2009, or cognitive consistency vs. understanding in Holbert et al., 2013).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
- Not checked — no full text of the sourcecites Kunda, 1990 source
- Supportedcites Hart et al., 2009 source
The Motivational Factors section says the meta-analysis confirmed that exposure decisions are guided by defense and accuracy motivation. The Closing Note says both motivations are important, and the Democracy and Selective Exposure section applies information selection to citizens’ political news choices. (LLM, conf=0.90)
- Not checked — no full text of the sourcecites Holbert et al., 2013 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“First, ideological reinforcement was examined by the correlation between affective candidate evaluations and political ideology which quantifies the extent to which the two are aligned as a function of the experimental treatment (Cho et al., 2018).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Measures
What the sources say
- Partly supportedcites Cho et al., 2018 sourceExperimental — accuracy not yet measured
The Results describe testing whether political expression strengthens the relationship between party identification and political opinions, and the Measures section describes affective ratings of candidates (page numbers unavailable). But the paper tests that relationship with regression models and tracks changes in candidate preference; it does not describe correlating candidate evaluations with ideology as a function of experimental treatment. (LLM, conf=0.86)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“People, in general, do not necessarily avoid counter-attitudinal information (Beam, 2014;Garrett et al., 2013), and further seek such information when they believe it helps them understand and be accurate on the situation at hand (Hart et al., 2009;Holbert et al., 2013;Kunda, 1990).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
What the sources say
- Not checked — no full text of the sourcecites Beam, 2014 source
- Not checked — no full text of the sourcecites Garrett et al., 2013 source
- Supportedcites Hart et al., 2009 source
The Abstract reports that an uncongeniality bias emerged when uncongenial information was relevant to accomplishing a current goal. The Closing Note also says accuracy motivation promotes accurate perceptions of reality. Together, these support the clause attributed to Hart et al.: people may seek counter-attitudinal information when it helps them reach an accurate understanding. (LLM, conf=0.90)
plainconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“in the ANCOVA model, political interest was added as a random factor and specified to interact with the fixed factor (i.e., conditions), and the results for the interaction were not significant.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Additional Analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A similar, albeit not statistically significant, the pattern was observed for all other measures of emotion.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Ideological Reinforcement
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one. The quote only partly states this claim.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The three-way interaction was not significant; likewise, two-way interactions involving interest were not significant either.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Additional Analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results of our experiment showed an overall pattern of opinion reinforcement and polarization after exposure to algorithm-recommended content, especially when algorithms were fed with self-generated search terms.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“With this motivation, individuals often cross ideological lines and glean (or at least do not avoid) information from the other side of the political spectrum (Garrett et al., 2013).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
- Not checked — no full text of the sourcecites Garrett et al., 2013 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“In contrast, the accuracy motivation drives individuals to seek information that they expect to be of high informational value.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
- Not checked — no full text of the sourcecites Garrett et al., 2013 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“The underlying reason for the reinforcing tendency of algorithms is that algorithms are naturally designed to operate with, not against, human tendencies, one of which is that people feel more comfortable with consistency and confirmation (Kunda, 1990).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Algorithmic Personalization
What the sources say
- Not checked — no full text of the sourcecites Kunda, 1990 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The input can be in the form of a search term or some other preference statement, and the selection is traditionally based on the personal history of the user (content-based filtering), or the cross-section of other users (collaborative filtering), or a mix of both (Balabanović & Shoham, 1997).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Algorithmic Personalization
What the sources say
- Not checked — no full text of the sourcecites Balabanović & Shoham, 1997 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As data about information search and consumption for a specific user accumulates, algorithms' ability to personalize is sharpened in subsequent searches.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Algorithmic Personalization
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Such user-oriented recommendations, in turn, increase the likelihood of consumption (clicking) by the users, as the recommended messages fit their interests.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“To the extent that user inputs (e.g., search terms, clicks, etc.) reflect their existing political preferences, search engine use could eventually lead to the so-called”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Algorithmic Personalization
What the sources say
- Not matchedcites Pariser, 2011
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“The directional (or defensive) motivation leads to selective exposure, encouraging individuals to seek information (or news sources) that they believe is congenial to their existing attitudes (Iyengar & Hahn, 2009;Stroud, 2011).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“Second, affective polarization was measured as the difference between affective evaluations of the two candidates which captures the degree to which attitudes about in-group and out-group candidates diverge.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Measures
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, algorithmic recommendations personalized by user behavior data, if unchecked, has the potential to solidify personal political convictions and encourage polarized opinions.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“These videos were used as a baseline controlsince they were the videos that a user who was in search for videos about the same topic (i.e., 410 the presidential election of past week)but did not have a specific search/watch history would encounter, per YouTube's recommendation at the time.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Experimental Procedure
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“Exposure to information that is more diverse or less agreeable in relation to one's own thoughts and beliefs could then lessen selfreinforcement and opinion polarization (Mutz, 2006).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
- Not checked — no full text of the sourcecites Mutz, 2006 source
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Non-self-report, behavioral data about user interests and beliefs allow algorithms to hone further recommendations.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
- The authors state this as an assumption: The terms that users enter for their online searches are reflective of what they care about and what they believe.
In the paper
“Further, attitude-consistent information (or information from a like-minded source) is often viewed as more credible and of higher quality, and this perception not only encourages consumption of the information but also facilitates the processing of it (Miller et al., 1993).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
- Not checked — no full text of the sourcecites Miller et al., 1993 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Due to the programmed responsiveness to past user interests and preferences, algorithms serve as a confirmatory communication partner or an echo chamber that reassures and reinforces users' prior beliefs and fosters extremism, as observed in the case of politically homogeneous communication networks.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When viewed from the broader literature in political psychology, this research on selective exposure suggests two ways how exposure to likeminded information via personalized algorithmic recommendations would shape users' political opinion: ideological reinforcement and affective polarization.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This suggests that ideological reinforcement, as indicated by the political emotion-ideology alignment, is heightened by political videos selected by the YouTube recommender algorithm based on participants' own search preferences and is muted to some degree if perceived preferences of participants' online social circle are used as inputs.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Ideological Reinforcement
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: Personalization by users' past behavior is a key mechanism of online search and recommender algorithms.
- Rests on an assumption: Algorithmic recommendations are a product of users' search terms and subsequent consumption of information.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“To summarize, algorithmic recommendations are largely an outcome of iterative interactions between users and algorithms, and the algorithmic recommendations are different depending on what search terms users enter.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In contrast, if a user's search term selection somehow goes beyond her routine repertoire, algorithms would provide more diverse recommendations.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“As social endorsement reduces partisan selectivity toward like-minded information, social media use is an opportunity to”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
- Not checked — no full text of the sourcecites Messing & Westwood, 2014 source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“First, schema theory in social cognition research has long suggested that human memory is a network of interconnected cognitive and affective constructs (Anderson & Bower, 1973;Lodge & Stroh, 1993).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
- Not matchedcites Anderson & Bower, 1973
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Lodge & Stroh, 1993 source
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, if individuals are motivated to explore ideas that they encounter in their social networks, their search behaviors would likely be less bounded by their own interests and preferences and thus train algorithms on its own.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Yet, given the human tendency toward psychological consistency (Kunda, 1990), cognitive salience of counter-attitudinal ideas in the user mind would not be strong enough to drive routine searches online.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
- Not checked — no full text of the sourcecites Kunda, 1990 source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Viewed in this light, algorithms, although helping users navigate a massive amount of information, add to political selectivity that separates people from contradictory views.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“It is a dynamic baseline, as the current YouTube environment simultaneously affects both the personalized recommendations and the trending videos.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Experimental Procedure
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“A general conclusion of past research on selective exposure is that exposure to confirmatory information strengthens existing opinions (Stroud, 2011;Sunstein, 2001;Tewksbury & Riles, 2015).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“That is, if searches are crafted based on one's perception (or memory) of ideas shared in social networks, the resulting algorithmic recommendations would likely contain a wider range of information or perspectives.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“If, as suggested by the notion of selective exposure, information search is driven by a user's own perspectives, algorithms recommend information the user would agree with.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The heightened selectivity as a result of the user-algorithm interaction induces a personally tailored information environment for each user which, in turn, shapes the user's opinion.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“In light of the schema theory, scholars of public opinion have posited that individuals' political opinion is often organized in a coherent structure of attitudes in which domain-specific opinions are grounded in a broader set of political beliefs (or”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A claim is checked only against the cited paper’s full text, never its abstract, and none is available for its sources.
In the paper
“If a person is exposed to counter-attitudinal information, her attitudinal ambivalence would increase, thereby reducing affective polarization (Huckfeldt et al., 2004;Mutz, 2006).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
What the sources say
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The first identifies”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Experimental Procedure
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one. The quote only partly states this claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Then, the consumption of proattitudinal information recommended by the algorithms gives reinforcing feedback to the algorithms, confirming the users' preferences and thus validating and enhancing algorithmic personalization.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > A Spiral of Selectivity and User Opinion
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“this approach only allows participants to indicate their preferences constrained within the list.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The relatively open social networks likely lead to a wider diversity of search terms gleaned from their online friends, which could potentially explain the results at least in part.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The results should be interpreted as showing algorithm effects when users are somehow motivated to explore ideas that they think their friends care about.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“this study utilized an actual real-world, not proxy, algorithm on a highly popular online platform, a fact that greatly enhances the external validity and relevance of the findings.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
In the paper
“As compared to the average population, college students are in general more active on the Internet and tend to be friends with a more diverse group of people on their online social networks (Pfeil et al., 2009).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
What the sources say
- Not checked — no full text of the sourcecites Pfeil et al., 2009 source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“we cannot draw a firm conclusion from a single experiment with college students.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Coupled with this research, our results suggest that algorithm effects on opinion reinforcement and polarization are conditional and would be better understood when considering how and to what extent cross-cutting exposure, as opposed to selective exposure, occurs.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“the complex and dynamic algorithmic systems handling big data make it difficult to predict outcomes (Lazer, 2015).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
What the sources say
- Not checked — no full text of the sourcecites Lazer, 2015 source
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This unique situation might amplify the reinforcing effects by algorithmic personalization as perhaps participants already have strong opinions and information recommended by algorithms might contain partisan or polarizing cues.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
- Rests on an assumption: The overall body of available information online about the election and candidates was highly polarized at the time when this experiment was conducted.
- Rests on an assumption: The opinion targets (presidential candidates) are much more salient and polarizing in participants' minds than any other issues.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“When it comes to controversial social and political topics, algorithmic personalization could also serve as an echo chamber strengthening users' prior convictions and thus aggravating the existing political chasm in society.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Conclusion
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“user opinion, in this study, was operationalized as affective assessments of two major candidates of the presidential election that was just finished.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Discussion
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“The first recommended video was selected based on previous evidence suggesting that users often click on top-ranked search results(Bakshy et al., 2015).”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Conclusion
What the sources say
- Not checked — no full text of the sourcecites Bakshy et al., 2015 source
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The authors state this as an assumption.
The terms that users enter for their online searches are reflective of what they care about and what they believe.
“A key assumption is that the terms that users enter for their online searches are reflective of what they care about and what they believe.”
The paper relies on this without support.
Personalization by users' past behavior is a key mechanism of online search and recommender algorithms.
“Although personalization by users' past behavior is a key mechanism, the complex and dynamic algorithmic systems handling big data make it difficult to predict outcomes (Lazer, 2015).”
The paper relies on this without support.
Algorithmic recommendations are a product of users' search terms and subsequent consumption of information.
“since algorithmic recommendations are a product of users' search terms and subsequent consumption of information.”
The paper relies on this without support.
The overall body of available information online about the election and candidates was highly polarized at the time when this experiment was conducted.
“the overall body of available information online about the election and candidates was also likely highly polarized at the time when this experiment was conducted.”
The paper relies on this without support.
The opinion targets (presidential candidates) are much more salient and polarizing in participants' minds than any other issues.
“It is thus highly likely that the opinion targets (i.e., presidential candidates) are much more salient and polarizing in participants' minds than any other issues.”
The paper relies on this without support.
Online platforms operating in different contexts program and run their algorithms differently.
“However, online platforms operating in different contexts program and run their algorithms differently.”
The paper relies on this without support.
Online search and recommender algorithms are essentially black boxes.
“This is why online search and recommender algorithms are essentially black boxes.”
Statistics recomputed
Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.
- ConsistentF(2, 104) = 4.47reported p < .05 · recomputed p = .014
“F(2, 104) = 4.47, p < .05”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Ideological Reinforcement
“the negative correlation across all conditions indicates, not surprisingly, that participants who identified themselves as liberal tend to feel less anger toward Clinton than toward Trump.”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Ideological Reinforcement
“control (r = .071,n.s.)”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Affective Polarization
“participants in the "social" condition reported a lower level of polarized affective assessments (M = 31.89,SD = 2.64) in terms of overall emotional valence (i.e., feeling thermometer) than those in the "self" condition (M = 39.87,SD = 2.74) and in the control condition (M = 42.88,SD = 2.75)”
§ Do Search Algorithms Endanger Democracy? An Experimental Investigation of Algorithm Effects on Political Polarization > Conclusion
“Entries are estimated marginal means with standard errors in parentheses.”
Citations
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“Yet, given the human tendency toward psychological consistency (Kunda, 1990), cognitive salience of counter-attitudinal ideas in the user mind would not be strong enough to drive routine searches online.”
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The role of (social) media in political polarization: A systematic review
Kubin, E., & von Sikorski, C. (2021) · Annals of the International Communication Association · doi:10.1080/23808985.2021.1976070 · Cited by 610
“Researchers found that YouTube algorithm recommendations (Cho et al., 2020), and exposure to social media comments that derogate political adversaries (Suhay et al., 2018) increases affective polarization.”
BackgroundExamining the consumption of radical content on YouTube
Hosseinmardi, H., Ghasemian, A., Clauset, A., Mobius, M., Rothschild, D. M., & Watts, D. J. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2101967118 · Cited by 171
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“…how social media platforms can recommend problematic content 92 and controlled experiments suggest algorithmic recommendations can alter the relative prevalence of conservative versus liberal information 93 , limit exposure to counter-attitudinal news 94 and have negative attitudinal effects 95 .”
Shin, D., Koerber, A., & Lim, J. S. (2025) · New Media & Society · doi:10.1177/14614448241234040 · Cited by 137
“…can fill the gap in research on user behaviors related to misinformation that previous studies have attempted to elucidate (e.g. Ahmed and Gil-Lopez, 2022; Cho et al., 2020; Hwang and Jeong, 2023; Kim et al., 2020; Melchior and Oliveira, 2022; Molina and Sundar, 2023; Tully et al., 2020).”
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Pedreschi, D., Pappalardo, L., Ferragina, E., Baeza-Yates, R., Barabási, A.-L., Dignum, F., Dignum, V., Eliassi-Rad, T., Giannotti, F., Kertész, J., et al. (2025) · Artificial Intelligence · doi:10.1016/j.artint.2024.104244 · Cited by 102
“Cho et al. [92] analysed factors leading to political polarisation on YouTube, finding that a recommender can contribute to this polarisation, but mainly through the channel of a user’s preference.”
AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review
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A Literature Review of Video-Sharing Platform Research in HCI
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AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review
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“Recent lab experiments confirm this insight by showing how algorithms can reinforce and polarize political opinions by iterating users’ past preferences (Cho et al., 2020).”
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Mitova, E., Blassnig, S., Strikovic, E., Urman, A., Hannák, A., de Vreese, C. H., & Esser, F. (2022) · Annals of the International Communication Association · doi:10.1080/23808985.2022.2142149 · Cited by 69
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“In the long term, this could contribute to increased polarization in society (Cho et al., 2020; Flaxman et al., 2016; Pariser, 2011).”
BackgroundSeven HCI Grand Challenges Revisited: Five-Year Progress
Stephanidis, C., Salvendy, G., Antona, M., Duffy, V. G., Gao, Q., Karwowski, W., Konomi, S., Nah, F. F., Ntoa, S., Rau, P. P., et al. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2450411 · Cited by 60
“The capability of algorithms in social media, e.g., filtering, hypernudging, and microtargeting, can be exploited for opinion manipulation (Cho et al., 2020; Christiano, 2022; Nguyen & Vu, 2019).”
Feminism, gender identity and polarization in TikTok and Twitter
Peña-Fernández, S., Ureta, A. L., & Morales-i-Gras, J. (2023) · Comunicar · doi:10.3916/c75-2023-04 · Cited by 41
“On Twitter, meanwhile, there is a greater presence of strategies and dynamics of polarized discourse and segregation, perhaps as a result of the use of algorithms which give rise to the formation of echo chambers and closed communities (Cho et al., 2020).”
Jones-Jang, S. M., & Chung, M. (2024) · New Media & Society · doi:10.1177/14614448221099591 · Cited by 43
“For example, a recent experiment found that YouTube algorithms recommend videos that reinforce viewers’ existing political opinion (Cho et al., 2020).”
BackgroundDemocratization in the age of artificial intelligence: introduction to the special issue
Cupać, J., Schopmans, H., & Ebetürk, I. (2024) · Democratization · doi:10.1080/13510347.2024.2338852 · Cited by 39
Kaluža, J. (2021) · Javnost - The Public · doi:10.1080/13183222.2021.2003052 · Cited by 28
“For example, Cho et al. (2020), who took into consideration the user activity expressed in speci fi c search terms (such as “ Crooked Hillary ” or “ Trump ’ s sexual assault ” ), observed a signi fi cant effect of bubble formation: “ due to the programmed responsiveness to past user interests and…”
BackgroundYoung, D. G., & Miller, J. M. (2023) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780197541302.013.15 · Cited by 39
Reranking partisan animosity in algorithmic social media feeds alters affective polarization
Piccardi, T., Saveski, M., Jia, C., Hancock, J., Tsai, J. L., & Bernstein, M. S. (2025) · Science · doi:10.1126/science.adu5584 · Cited by 34
“Some studies support this hypothesis, finding that online interactions exacerbate polarization ( 27 ), potentially because of the increased visibility of hostile political discussions ( 28 ), divisive language ( 29 – 33 ), and content that reinforces existing beliefs ( 34 ).”
Kantian Ethics and the Attention Economy
Aylsworth, T., & Castro, C. (2024) · Springer eBooks · doi:10.1007/978-3-031-45638-1 · Cited by 30
Wang, X., & Shang, Q. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104369 · Cited by 48
Public knowledge of alternative media in times of algorithmically personalized news
Klawier, T., Prochazka, F., & Schweiger, W. (2021) · New Media & Society · doi:10.1177/14614448211021071 · Cited by 29
“Mechanisms operating on these platforms are likely to underlie the same basic logic of pushing attention-grabbing messages, favoring polarizing content (Cho et al., 2020; Schweiger et al., 2019).”
BackgroundLudwig, K., Grote, A., Iana, A., Alam, M., Paulheim, H., Sack, H., Weinhardt, C., & Müller, P. (2023) · Social Science Computer Review · doi:10.1177/08944393221149290 · Cited by 44
“On the other hand, Cho et al. (2020) found YouTube ’ s algorithmic recommendations of political videos, based on the participants ’ search preferences, to affectively polarize users.”
BackgroundLiu, N., Hu, X. E., Savas, Y., Baum, M., Berinsky, A. J., Chaney, A. J. B., Lucas, C., Mariman, R., Benedictis-Kessner, J. D., Guess, A. M., et al. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2318127122 · Cited by 23
YouTube’s recommendation algorithm is left-leaning in the United States
Ibrahim, H., AlDahoul, N., Lee, S., Rahwan, T., & Zaki, Y. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgad264 · Cited by 21
“Nonetheless, there have been several influential studies which aimed to classify YouTube videos into distinct categories (22–25), as well as understand potential radicalization pathways influenced by the recommendation algorithm (21, 26–28).”
BackgroundKilling the golden goose? A framework for regulating disruptive technologies
Bennett, W. L. (2023) · Information, Communication & Society · doi:10.1080/1369118x.2021.1994625 · Cited by 21
“In the political arena, the same proprietary algorithms that make companies so pro fi table also promote user engagement with the polarizing and in fl ammatory content that advocates for democracy, civility and human rights want to regulate (Cho et al., 2020; Tufekci, 2018).”
BackgroundAhmed, S., Madrid‐Morales, D., & Tully, M. (2022) · Online Information Review · doi:10.1108/oir-11-2021-0634 · Cited by 18
Self-citationAhmed, S., & Gil‐López, T. (2022) · Journalism & Mass Communication Quarterly · doi:10.1177/10776990221110113 · Cited by 21
“Cho et al.’s (2020) experimental results lend credence to the premise that heightened selectivity, as a result of the user–algorithm interaction, and user opinion mutually reinforce each other through YouTube’s personalized algorithmic recommendations.”
InfluentialSelf-citationDoes algorithmic filtering lead to filter bubbles in online tourist information searches?
Gong, Y., Schroeder, A., Pan, B., Sundar, S. S., & Mowen, A. J. (2023) · Information Technology & Tourism · doi:10.1007/s40558-023-00279-4 · Cited by 25
“This finding supports our scenario, as previous empirical studies have found that personalization algorithms can reinforce polarized opinions (Cho et al. 2020; Rhodes 2022).”
Calderon, E. D. V., James, T. L., & Lowry, P. B. (2023) · Data and Information Management · doi:10.1016/j.dim.2023.100042 · Cited by 18
“Much has been made of Facebook’s newsfeed algorithm’s potential to influence the democratic process, but everyday phenomena, such as how much one pays for products on Amazon or for a ride on Uber (i.e., dynamic pricing), are also subject to algorithmic decisions [22, 31, 32, 38, 121].”
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Huang, B. (2024) · Current Psychology · doi:10.1007/s12144-024-06106-1 · Cited by 15
“The impact of this divergence in access to information is profound (Cho et al., 2020 ).”
The effect of media on opinion formation
Lee, W., Yang, S.-G., & Kim, B. J. (2022) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2022.127075 · Cited by 15
Kelm, O., Neumann, T., Behrendt, M., Brenneis, M., Gerl, K., Marschall, S., Meißner, F., Stefan Harmeling, B., Vowe, G., & Ziegele, M. (2023) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2023.100343 · Cited by 31
Protected how? Problem representations of risk in the General Data Protection Regulation (GDPR)
Padden, M., & Öjehag‐Pettersson, A. (2021) · Critical Policy Studies · doi:10.1080/19460171.2021.1927776 · Cited by 26
“…worthiness of ‘public interest’ is likely to become less so in societies characterized by increasing polarization, which has been shown, ironically, to be heightened by ‘recommender algorithms’ used by streaming services such as YouTube and which are based on user profiles (Cho et al. 2020).”
BackgroundMethodYu, H., Ryoo, Y., & Han, E. (2023) · Internet Research · doi:10.1108/intr-09-2021-0677 · Cited by 14
Prefrontal suppression in short-video viewing: unraveling the neural correlates of self-controlPreprint
Su, C., Teng, B., Zhou, H., Geng, F., & Hu, Y. (2023) · medRxiv · doi:10.1101/2023.10.30.23296738 · Cited by 14
“If not properly monitored, algorithmic recommendations tailored based on user’s behavior might have the potential to influence democracy, privacy and mental health 73,74 .”
BackgroundPolarization in Social Media: A Virtual Worlds-Based Approach
Jacob, D., & Banisch, S. (2023) · Journal of Artificial Societies and Social Simulation · doi:10.18564/jasss.5170 · Cited by 12
Affective Political Polarization and Hate Speech: Made for Each Other?
Стукал, Д., Ахременко, А. С., & Petrov, A. (2022) · RUDN Journal of Political Science · doi:10.22363/2313-1438-2022-24-3-480-498 · Cited by 13
Hu, A., & Ou, M. (2025) · Telematics and Informatics · doi:10.1016/j.tele.2025.102291 · Cited by 18
Coppolillo, E., Mungari, S., Ritacco, E., Fabbri, F., Minici, M., Bonchi, F., & Manco, G. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104125 · Cited by 16
Epstein, R., & Flores, A. (2024) · PLoS ONE · doi:10.1371/journal.pone.0303036 · Cited by 15
Ethical ambiguity and complexity: tech workers’ perceptions of big data ethics in China and the US
Di, D. (2023) · Information Communication & Society · doi:10.1080/1369118x.2023.2166357 · Cited by 10
“Perhaps most worrying is that some tech companies are cavalier about data privacy (Fu, 2019), particularly those that depend for their revenues on signi fi cant social discord and polarization (Cho et al., 2020; Wang, 2015).”
BackgroundMattis, N. M., Masur, P. K., Möller, J. E., & van Atteveldt, W. (2021) · doi:10.31235/osf.io/wvxf5 · Cited by 9
Public Service Media in the Age of Platformization of Culture and Society
Baldini, T. B., López, J. M. T., & Barrientos–Báez, A. (2021) · Palgrave global media policy and business · doi:10.1007/978-3-030-56466-7_3 · Cited by 10
Zhu, Z., Zhang, N., Ding, M., & Chen, L. (2023) · Information Systems Journal · doi:10.1111/isj.12486 · Cited by 11
“Algorithms can thus reduce political selectivity if the range of search terms goes beyond users' political beliefs and identity (Cho et al., 2020; Rekker, 2021).”
BackgroundLee, S., & Kim, K. (2023) · Mass Communication & Society · doi:10.1080/15205436.2023.2272846 · Cited by 10
“As news media systems and journalism practices have changed considerably (e.g., increased user selectivity, algorithmic recommendations, and proliferation of partisan media), it is easier for citizens to encounter partisan news (Bennett & Iyengar, 2008; Cho et al., 2020; Stroud, 2011).”
Sun, M., & Meng, S. (2023) · Youth & Society · doi:10.1177/0044118x231162875 · Cited by 11
“There are concerns, especially in the west, about algorithm-induced ideo-logical polarization through the self-reinforcement of users’ opinions or the dissemination of extremist propaganda (Cho et al., 2020).”
BackgroundHe, J., Gao, B., & Wang, Y.-T. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2423334 · Cited by 10
“Through precise algorithmic recommendations, users’ satisfaction with media content experiences is heightened, which in turn strengthens the PSI relationship between users and media figures (Cho et al., 2020).”
The Authority to Moderate: Social Media Moderation and its Limits
Kashyap, B., & Formosa, P. (2023) · Philosophy & Technology · doi:10.1007/s13347-023-00685-w · Cited by 8
“…undermine and disrespect user autonomy (Sahebi & Formosa, 2022), lead to widespread and serious mental health issues in vulnerable populations, especially young people (Klein, 2023), and promote the circulation of misinformation (Barnes, 2022) and magnify affective polarisation (Cho et al., 2020).”
BackgroundLudwig, K., Müller, P., Nikolajevic, N., & Grote, A. (2025) · Information Communication & Society · doi:10.1080/1369118x.2024.2435998 · Cited by 13
“The relatively small effect sizes of the present experiment are in line with other studies using real NRS as stimuli (Cho et al., 2020; Kelm et al., 2023) and may not be directly comparable to those of classical experiments.”
Allen, L. K., DeLiema, D., & Kendeou, P. (2025) · Educational Psychologist · doi:10.1080/00461520.2025.2588213 · Cited by 7
“Algorithms reinforce existing opinions by interacting with users’ search terms (Cho et al., 2020), shaping selective news exposure along political lines (Flamino et al., 2023; Guess, 2021), and amplifying ideologically specific social media spaces (Corsi, 2024; Quelle & Bovet, 2025).”
Socializing the political: rethinking filter bubbles and social media with Hannah Arendt
Daus, Z. (2024) · Ethics and Information Technology · doi:10.1007/s10676-024-09759-5 · Cited by 10
People see what they want to see: an EEG study
Yu, H., & Han, E. (2023) · Cognitive Neurodynamics · doi:10.1007/s11571-023-09982-8 · Cited by 6
“…amount of information available online, search engines have become important drivers of how people navigate online, and recommendations based on big data and algorithms are increasingly key to how most users explore, select, and consume information (Beam 2014; Cho et al. 2020; Ricci et al. 2011).”
Mikhaylova, O. R. (2022) · New Media & Society · doi:10.1177/14614448221099172 · Cited by 6
“Because not all vloggers can comply with YouTube’s standards, inequalities are reproduced (Bishop, 2018; Cho et al., 2020).”
BackgroundRomaní, C. C., & Rivera-Vargas, P. (2022) · doi:10.31235/osf.io/yanzw · Cited by 6
Infodemics on Youtube: Reliability of Content and Echo Chambers on COVID-19 (Preprint)Preprint
Marco, N. D., Cinelli, M., & Quattrociocchi, W. (2021) · doi:10.2196/preprints.32258 · Cited by 6
“, loops of extreme/questionable contents reinforced by the algorithm and by individual choices in a sort of vicious circle, is still strongly disputed [35, 36, 37, 38, 39, 40].”
BackgroundBassi, D., Maggini, M. J., Vieira, R. L. R., & Pereira-Fariña, M. (2024) · International Conference on Social Networks Analysis, Management and Security (SNAMS) · doi:10.1109/snams64316.2024.10883781 · Cited by 5
“Furthermore, this polarization could be reinforced by algorithmic recommendation systems that may inadvertently amplify extreme viewpoints [26].”
Lee, S., & Cho, J. (2023) · International Journal of Public Opinion Research · doi:10.1093/ijpor/edad020 · Cited by 5
Self-citationLiao, M. (2023) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2023.2206662 · Cited by 7
“These so-called algorithmic gatekeepers decide the visibility and salience of news content primarily based on user preferences (Cho et al., 2020).”
BackgroundResultInfluentialChernilo, D. (2022) · European Journal of Social Theory · doi:10.1177/13684310221135500 · Cited by 5
“But if they fall short on either technical or ethical grounds, then democratic legitimacy itself suffers reputational costs, which may then be construed as yet another source of its chronic flaws (Cho et al., 2020).”
BackgroundZafrilla, P. J. P. (2022) · Opinião Pública · doi:10.1590/1807-0191202228133 · Cited by 9
Andaluz, J. S., & Rodríguez-Gordo, C. (2021) · Cuadernos salmantinos de filosofía · doi:10.36576/summa.144497 · Cited by 5
“Funny Weapons”: The Norms of Humour in the Construction of Far‐Right Political Polarisation
Toscano, G. B., & Villanueva, C. F. (2025) · Social Inclusion · doi:10.17645/si.10211 · Cited by 4
Análisis de la campaña de desinformación en las Elecciones Brasileñas de 2022
del Vas, R. S., Ruiz-Incertis, R., Acosta, D. G., et al. (2025) · Doxa Comunicación Revista interdisciplinar de estudios de comunicación y ciencias sociales · doi:10.31921/doxacom.n41a2320 · Cited by 4
Segerberg, A., & Magnani, M. (2025) · PLoS ONE · doi:10.1371/journal.pone.0318338 · Cited by 4
“They respond to signals of salience and urgency in engagement metrics and trend tickers [45–47].”
Social Media and Political Polarization: A Panel Study of 36 Countries from 2014 to 2020
Lu, J., Sun, M., & Liu, Z. (2024) · Social Indicators Research · doi:10.1007/s11205-024-03367-y · Cited by 7
“Meanwhile, affective polarization was induced by algorithm recommendation (Cho et al., 2020) and linkage with the accounts of political opponents (Suhay et al., 2018; Allcott et al., 2020).”
Masood, M., Skoric, M. M., & Ahmed, S. (2023) · Journal of Broadcasting & Electronic Media · doi:10.1080/08838151.2023.2298274 · Cited by 8
“Discourse supporting the construction of the temple and, in general, the rights of religious minorities were notably visible online (Ahmed, 2020; Tanzeem, 2020).”
BackgroundSelf-citationPacchioni-Hurtado, V., & Antezana, M. (2023) · Cuadernos del Centro de Estudios de Diseño y Comunicación · doi:10.18682/cdc.vi194.9620 · Cited by 6
Epstein, R., & Flores, A. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4527207 · Cited by 3
Lu, Q., Chen, T., Duan, H., Zhou, X., & Lin, Z. T. (2026) · Journal of Travel Research · doi:10.1177/00472875261441570 · Cited by 4
Soft Power Is Bullshit! How Shared Interests, Not Values, Shape International Relations
Manor, I., & Golan, G. J. (2026) · American Behavioral Scientist · doi:10.1177/00027642251407781 · Cited by 3
Liu, Z.-G. Y. W. J. J.-C. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13760-w · Cited by 5
“Algorithms from social media and news websites shape the content you will view by assuming what you like based on your previous preferences and interactions; therefore, you are more likely to take in information that supports your previous viewpoint (Cho et al., 2020).”
van der Breggen, M. M., Gonçalves, J., & Boeren, D. (2025) · Journal of Information Technology & Politics · doi:10.1080/19331681.2025.2544653 · Cited by 4
Jiang, T., Sun, Z., & Fu, S. (2025) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24988 · Cited by 7
“Therefore, the concept of filter bubbles reflects the potential negative consequences of human – algorithm interactions, rather than being solely a biased algorithmic outcome (Areeb et al., 2023; Cho et al., 2020).”
Heiler, P. (2024) · Journal of Econometrics · doi:10.1016/j.jeconom.2024.105856 · Cited by 3
Huang-Isherwood, K. M., Cho, J., Hong, J.-W., & Lee, E. (2024) · Social Science Computer Review · doi:10.1177/08944393241252027 · Cited by 3
“Moreover, fi lter bubbles refer to the vicious cycle of personalized algorithms, including the role of conversational agents, in keeping one bound to past groups and content, and further recommending similar domains without departing from them (Cho et al., 2020; Ojeda, 2021).”
Self-citationCuéllar Rivero, R. (2024) · Revista Española de Ciencia Política · doi:10.21308/recp.64.07 · Cited by 3
Lee, S. S., & Kang, S.-W. (2024) · Korean Journal of Journalism & Communication Studies · doi:10.20879/kjjcs.2024.68.1.010 · Cited by 3
Lee, S. Y., Lee, H., & Park, S. (2024) · International Journal of Public Opinion Research · doi:10.1093/ijpor/edae050 · Cited by 3
Zanetti, L. A., Luvizotto, C. K., Nascimento, F. A., & Trindade, A. C. (2023) · doi:10.11648/j.ss.20231204.11 · Cited by 3
Dorjee, D. (2021) · MindRxiv (OSF Preprints) · doi:10.31231/osf.io/qtkyr · Cited by 3
Virality, Algorithms, and Illiberal Attacks on the Press: Legitimation Strategies for a New World
Jacobs, R. N. (2020) · Scholars Archive - University at Albany (University at Albany, State University of New York) · doi:10.6092/issn.1971-8853/11190 · Cited by 3
“The user is likely to click on these algorithmically provided links, because they confirmpreexisting biases and interests; when they do this, the algorithm feeds them even more of this kind of content, resulting in ever more narrow and selective exposure (Cho et al., 2020).”
BackgroundClickbait Culture in Internet Journalism: The Digital Way of “Selling News”
Ercan, E. E. (2026) · SELÇUK ÜNİVERSİTESİ İLETİŞİM FAKÜLTESİ AKADEMİK DERGİSİ · doi:10.18094/josc.1697014 · Cited by 3
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Impact of YouTube User‐Generated Content on News Dissemination and Youth Information Reception
Chunqiong, W., Shan, J., Jianhong, S., & Yingqi, L. (2025) · Health Expectations · doi:10.1111/hex.70408 · Cited by 2
The power of cross-cultural communication: reception and impact of Chinese variety shows on YouTube
Zhang, Y. (2025) · Frontiers in Communication · doi:10.3389/fcomm.2025.1542139 · Cited by 2
Strikovic, E., Blassnig, S., Mitova, E., Urman, A., Esser, F., & de Vreese, C. H. (2024) · New Media & Society · doi:10.1177/14614448241263765 · Cited by 8
“However, until now, algorithmic literacy in the context of NRS has not been the focus of research (see Cho et al., 2020; Gran et al., 2021 for exceptions).”
Misinformation Processing Model: How Users Process Misinformation When Using Recommender Algorithms
Shin, D. (2024) · Springer eBooks · doi:10.1007/978-3-031-52569-8_5 · Cited by 2
Misinformation and Generative AI: How Users Construe Their Sense of Diagnostic Misinformation
Shin, D. (2024) · Springer eBooks · doi:10.1007/978-3-031-52569-8_9 · Cited by 3
Zumofen, G. (2023) · Journal of Information Technology & Politics · doi:10.1080/19331681.2023.2221681 · Cited by 2
“Similarly, Cho, Ahmed, Hilbert, Liu, and Luu (2020) experimentally manipulated a real-world search engine.”
InfluentialGriesser, S., Ricklin, A., Kälin, R., & Lu, G. (2023) · IEEE Swiss Conference on Data Science (SDS) · doi:10.1109/sds57534.2023.00026 · Cited by 2
“In fact, more polarising information is viewed more frequently [3] and receives more comments [4].”
BackgroundA K-means Optimized Self-Organizing Map Neural Network Video Recommendation Framework
Liming, Y., & Tianyao, L. (2023) · doi:10.1109/icetci57876.2023.10176756 · Cited by 2
“Therefore, users need to spend a lot of time and effort to search for information, which results in unsatisfactory service [1]–[3].”
BackgroundArandjelović, O. (2023) · Social Sciences · doi:10.3390/socsci12030173 · Cited by 1
Rentsch, S. (2023) · Sozialwissenschaften und Berufspraxis · doi:10.1007/978-3-658-38268-1_2 · Cited by 2
Son, W.-C. (2022) · Philosophy & Technology · doi:10.1007/s13347-022-00573-9 · Cited by 2
“Viewed in this light, algorithms, while helping users navigate a massive amount of information, add to politi‑ cal selectivity that separates people from contradictory views (Cho et al., 2020: 165‑166).”
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Processos de Escolha Política, Mediação Anti-democrática e Ambientes Digitais
Conci, L. G. A., & Lopes, J. G. M. (2021) · Direito Público · doi:10.11117/rdp.v18i99.5743 · Cited by 2
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Metadata
- Authors
- Cho, J., Ahmed, S., Hilbert, M., Liu, B., & Luu, J.
- Affiliations
- University of California, Davis (US)
- Nanyang Technological University (SG)
- Software Engineer, Sacramento, CA, USA
- Software Engineer, San Diego, CA, USA
- Corresponding author
- Cho, Jaeho
- Venue
- Journal of Broadcasting & Electronic Media
- Publisher
- Informa UK Limited
- Published
- 2020-04-27
- Volume
- 64
- Issue
- 2
- Pages
- 150-172
- ISSN
- 0883-8151 (ISSN-L)
- 1550-6878
- OpenAlex
- W3018249611
- Cited by
- 164
- References
- 54
- Citations by year
- 2026: 21 · 2025: 33 · 2024: 33 · 2023: 38 · 2022: 20 · 2021: 17 · 2020: 2
- FWCI
- 23.10
- Type
- journal article
- Language
- en
- Open access
- green
- escholarship.org
- Locations
- Journal of Broadcasting & Electronic Media (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Topics
- Social Sciences › Communication › Social Media and Politics
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- algorithmic recommendation, political polarization, YouTube, affective polarization, algorithmic personalization, democracy
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