Social Media and Morality.

In the paper

“social media posts that contain moral emotional language are more likely to be shared on social media than those that do not contain moral emotional language (Brady et al. 2017)”

What the sources say

• Partly supported

  The Results report that moral-emotional language predicted higher retweet rates across tweets about gun control, same-sex marriage, and climate change. The Discussion likewise describes increased transmission of political tweets, but the cited study does not establish the claim for social media posts generally. (LLM, conf=0.83)

  cites Brady et al. 2017 sourceExperimental — accuracy not yet measured

In the paper

“the absence of nonverbal cues that are essential in face-to-face communication may exaggerate the perceived intensity of users' outrage (Lieberman & Schroeder 2020)”

What the sources say

• Partly supported

  The “Fewer nonverbal cues online” section (page not provided) says text-based platforms lack nonverbal cues and that reading opinions rather than hearing them can impair judgments of a communicator’s feelings. The “Greater anonymity online” section separately discusses moral outrage on social media. Neither passage says that missing cues exaggerate the perceived intensity of users’ outrage. (LLM, conf=0.84)

  cites Lieberman & Schroeder 2020 sourceExperimental — accuracy not yet measured

In the paper

“people nevertheless perceive online discussions to be far more hostile (Bor & Petersen 2022)”

What the sources say

• Supported

  The Results (page unavailable) describe a documented hostility gap in assessments of overall discussion climates: people perceive online political discussions as more hostile than offline ones. The paper distinguishes this from assessments of discussions people personally participate in, which they do not perceive as more severe online. (LLM, conf=0.90)

  cites Bor & Petersen 2022 source

In the paper

“one online experiment found that some people who are exposed to opposing partisan accounts on social media actually experience a backfire effect, such that they become more entrenched in their own beliefs (Bail et al. 2018)”

What the sources say

• Supported

  The Abstract reports that Republican participants expressed substantially more conservative views after following a bot that shared opposing political messages. The Discussion and Conclusion explicitly calls this a backfire effect among Republican respondents, supporting the claim's qualified wording, “some people.” (LLM, conf=0.93)

  cites Bail et al. 2018 source

In the paper

“mentioning an out-group member is the strongest predictor of social media engagement out of a variety of predictors measured in an analysis of Facebook and Twitter posts (N = 2,730,215) by politicians and partisan news media sources (Rathje et al. 2021)”

What the sources say

• Supported

  The Discussion reports 2,730,215 Facebook and Twitter observations and identifies out-group language as the most important predictor of sharing in posts from news media accounts and politicians. The Results sections for major media outlets and Congress members likewise report that out-group language ranked highest among the key predictors measured. (LLM, conf=0.94)

  cites Rathje et al. 2021 source

In the paper

“aggressive individuals appear to act equally aggressive in both offline and online contexts (Bor & Petersen 2022)”

What the sources say

• Supported

  The Results report equal average self-reported hostility in online and offline political discussions and a high within-person correlation (r = 0.84). The Conclusions and General Discussion likewise describe hostile individuals as engaging in political hostility in both contexts. (LLM, conf=0.91)

  cites Bor & Petersen 2022 source

In the paper

“People who engage in aggressive and hostile behaviors in the offline world are also likely to do so in the online world, where their actions are accelerated by the structure of the Internet (Bor & Petersen 2022;Kowalski et al. 2014Kowalski et al. , 2019))”

What the sources say

• Partly supported

  The Conclusions and General Discussion say that individuals motivated by status and dominance engage in hostility in both online and offline political discussions. Study 8 and the Conclusions attribute the greater apparent online hostility to the Internet’s connectivity, which makes hostile actions more visible and gives them greater reach. They do not say that the Internet accelerates the actions themselves, and the findings concern political hostility rather than aggressive behavior generally. (LLM, conf=0.86)

  cites Bor & Petersen 2022 sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites Kowalski et al. 2014 source
• ?Not checked — no full text of the sourcecites Kowalski et al. 2019 source

In the paper

“Studies suggest that feelings of marginalization coupled with dominance orientation make people more likely to engage in hostility on social media (Bor & Petersen 2022, Petersen et al. 2023)”

What the sources say

• Partly supported

  The Results (page not provided) find that hostility increases with status-driven risk taking in online political discussions. The Conclusions and General Discussion (page not provided) also describe status and dominance as motives for hostility. Neither passage supports the added claim that feelings of marginalization are coupled with dominance orientation. (LLM, conf=0.88)

  cites Bor & Petersen 2022 sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites Petersen et al. 2023 source

In the paper

“Because there is such a large volume of people to connect with in the online context, there are significantly more extreme voices to affiliate with than there were in prior social groups that were limited by geography (Petersen et al. 2020, Törnberg 2022).”

What the sources say

• ?Not checked — no full text of the sourcecites Petersen et al. 2020 source
• Partly supported

  The Discussion (page not provided) says digital media connect people outside their local social bubbles, supporting the comparison with geographically limited groups. It does not say that online networks offer significantly more extreme voices to affiliate with; the paper instead explains polarization through nonlocal interaction and partisan sorting. (LLM, conf=0.85)

  cites Törnberg 2022 sourceExperimental — accuracy not yet measured

In the paper

“Part of this trend might be explained by the Internet's informing users about government corruption (Zhuravskaya et al. 2020).”

What the sources say

• Partly supported

  Section 2.1 reports that expanding 3G coverage benefited populist opposition parties in Europe. It also says mobile Internet exposed government corruption and suggests that informing voters explains part of its effect on government approval in a global analysis. The review does not establish that corruption information explains the specifically European populist-vote trend. (LLM, conf=0.82)

  cites Zhuravskaya et al. 2020 sourceExperimental — accuracy not yet measured

In the paper

“One study of fake news sharing on Twitter found that partisan polarization is the primary psychological motivation behind fake news sharing”

What the sources say

• Supported

  The paper’s title states the claim directly. Its Abstract (page not provided) reports strong support for the partisan-polarization explanation and finds that people who hate their political opponents are most likely to share political fake news. The citing sentence correctly identifies this as a study of Twitter sharing. (LLM, conf=0.94)

  cites Osmundsen et al. 2021 source

In the paper

“People also tend to overestimate the degree of polarization (Levendusky & Malhotra 2016, Westfall et al. 2015) and animosity (Mernyk et al. 2022, Ruggeri et al. 2021) between political groups, which may be exacerbated by the abundance of divisive content they see online.”

What the sources say

• Supported

  The Abstract reports that Americans significantly misperceive the public as more divided along partisan lines than it is. The section “Americans Perceive Greater Polarization Than Actually Exists” also reports a statistically significant gap between perceived and actual polarization. The cited paper supports the polarization portion of the sentence; this citation is not attached to the separate claims about animosity or online content. (LLM, conf=0.94)

  cites Levendusky & Malhotra 2016 source
• ?Not checked — no full text of the sourcecites Westfall et al. 2015 source

In the paper

“This may lead conspiracy believers to self-select into online communities that in turn share and reinforce their beliefs (Robertson et al. 2022).”

What the sources say

• Supported

  The New Directions section says people facing identity threats may cluster in online communities that support an identity-protective worldview, and that conspiracy theories may spread widely online. This supports the citing sentence’s hedged account of joining communities that share and reinforce those beliefs; the paper presents it as a possibility, not an established causal finding. (LLM, conf=0.87)

  cites Robertson et al. 2022 source

In the paper

“People also tend to overestimate the degree of polarization (Levendusky & Malhotra 2016, Westfall et al. 2015) and animosity (Mernyk et al. 2022, Ruggeri et al. 2021) between political groups, which may be exacerbated by the abundance of divisive content they see online.”

What the sources say

• Partly supported

  The Results (Studies 1 and 2) show that Democrats and Republicans overestimated rival partisans’ support for violence. That supports an overestimation of a specific hostile attitude, but the paper does not establish that people generally overestimate animosity between political groups. (LLM, conf=0.82)

  cites Mernyk et al. 2022 sourceExperimental — accuracy not yet measured
• Supported

  The Conclusion (page not available in our copy) says people are likely to overestimate how negatively political out-groups perceive actions initiated by their side and exaggerate the magnitude of differences between groups. This supports the cited claim about perceived animosity; the paper does not need to support the citing sentence’s separate suggestion about online content. (LLM, conf=0.87)

  cites Ruggeri et al. 2021 source

In the paper

“Another potential consequence of the spread of moral and emotional content online is increased polarization (Iyengar et al. 2019).”

What the sources say

• Partly supported

  The ‘Origins and Causes of Affective Polarization’ section (pp. 6–7) describes hostile partisan content and says social networks can amplify polarizing messages. It supports online content as a potential contributor to polarization, but does not specifically identify the spread of moral and emotional content online as the contributor. (LLM, conf=0.83)

  cites Iyengar et al. 2019 sourceExperimental — accuracy not yet measured

In the paper

“Additionally, true news is more likely to generate engagement than false news on Reddit (Bond & Garrett 2023).”

What the sources say

• Partly supported

  The Discussion reports lower engagement for fact-checked Reddit posts whose information was false than for those whose information was true. The claim omits that the study examined posts eliciting fact-checking comments, so it extends the finding to Reddit news generally. (LLM, conf=0.86)

  cites Bond & Garrett 2023 sourceExperimental — accuracy not yet measured

In the paper

“Other research suggests that misinformation spread on Twitter is linked to lower county-level vaccine uptake (Pierri et al. 2022), and people who got their news primarily from”

What the sources say

• Partly supported

  The Results report that Twitter misinformation was significantly correlated with county-level vaccine hesitancy. The Methods distinguish that outcome from vaccination uptake, which the study measured only at the state level; the cited paper therefore does not establish lower county-level uptake. (LLM, conf=0.91)

  cites Pierri et al. 2022 sourceExperimental — accuracy not yet measured

In the paper

“Americans with anti-vaccine and pro-vaccine attitudes clustered into distinct echo chambers on Twitter (Rathje et al. 2022).”

What the sources say

• Supported

  In Study 1’s Network analysis (page unavailable), the paper reports two distinct Twitter network communities in the US. US participants in one community were significantly less vaccine-confident than those in the other, supporting the claim that people with differing vaccine attitudes clustered into distinct echo chambers. (LLM, conf=0.92)

  cites Rathje et al. 2022 source

In the paper

“Other research has found a causal link between exposure to vaccine misinformation and reduced intentions to get vaccinated (Loomba et al. 2021).”

What the sources say

• Supported

  The paper’s opening section describes a randomized controlled trial in the UK and USA and reports that exposure to COVID-19 vaccine misinformation reduced vaccination intent relative to factual information. Its later caution that the design does not allow causal inferences concerns the effects of different types of misinformation, not the overall comparison between the randomized groups. The finding is about stated intent under the study’s exposure conditions, not actual vaccination. (LLM, conf=0.88)

  cites Loomba et al. 2021 source

In the paper

“Many studies have found that misinformation and moral outrage are often closely intertwined (Marie et al. 2023, Vosoughi et al. 2018).”

What the sources say

• Partly supported

  The Discussion of Experiments 1–4 reports that moralizing a political issue amplified participants’ willingness to share politically congruent news, including fake news. That supports a link between moralization and misinformation sharing, but the paper does not establish a link specifically with moral outrage or show that the two are often intertwined. (LLM, conf=0.83)

  cites Marie et al. 2023 sourceExperimental — accuracy not yet measured
• ?Not checked — no full text of the sourcecites Vosoughi et al. 2018 source

In the paper

“For instance, polarized rhetoric about the pandemic on Twitter was highly correlated with polarized beliefs about the risks of the pandemic several days later (Simchon et al. 2022).”

What the sources say

• Partly supported

  The Dictionary validation section reports a strong correlation (r = 0.67) between polarized COVID-19 language on Twitter and partisan differences in pandemic concern at an eight-day offset. It does not clearly support the claimed direction of that offset: the passage specifies poll responses at t0 and Twitter language at t8, rather than beliefs occurring several days after the tweets. (LLM, conf=0.82)

  cites Simchon et al. 2022 sourceExperimental — accuracy not yet measured

In the paper

“Early in the COVID-19 pandemic, attitudes and behavior related to the pandemic were especially polarized, with Republicans and Democrats in the United States having strikingly different attitudes about public health behaviors and the COVID-19 vaccine (Gollwitzer et al. 2020, Van Bavel et al. 2023).”

What the sources say

• Partly supported

  Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites Gollwitzer et al. 2020 sourceExperimental — accuracy not yet measured
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Van Bavel et al. 2023

In the paper

“Because social media platforms allow information to spread with less friction than in traditional news outlets, such as newspapers or television news, misinformation and conspiracy theories are able to go rapidly viral (Robertson et al. 2022, Van Bavel et al. 2021a, van der Linden et al. 2021).”

What the sources say

• Partly supported

  The Introduction says internet and social media let conspiracy theories spread through large communities, and New Directions says they may go viral online. The paper does not compare social media with newspapers or television, attribute the spread to lower friction, or establish that misinformation generally goes rapidly viral. (LLM, conf=0.86)

  cites Robertson et al. 2022 sourceExperimental — accuracy not yet measured
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Van Bavel et al. 2021a
• ?Not checked — no full text of the sourcecites van der Linden et al. 2021 source

In the paper

“For example, deleting Facebook during genocide remembrance week in Bosnia actually increased ethnic polarization, especially if people had particularly homogeneous offline social networks (Asimovic et al. 2021).”

What the sources say

• Partly supported

  The Abstract and Research Design report that deactivating Facebook during the Srebrenica genocide commemoration week led to more negative attitudes toward ethnic outgroups. The Discussion finds a stronger effect among residents of ethnically homogeneous towns, but uses town composition as a proxy for offline networks; that analysis was not preregistered. The claim presents homogeneous offline networks as an established individual-level condition rather than a tentative inference from where participants lived. Page numbers were not provided in our copy. (LLM, conf=0.85)

  cites Asimovic et al. 2021 sourceExperimental — accuracy not yet measured

In the paper

“The large majority of published research has focused on North American and European issues and samples.”

What the sources say

• ?Could not verify

  The Results section lists a “Country of sample” heading, and the appendix codebook lists “Country of sample” and “Political topic,” but the available passages give no findings under those headings. Searches for North American and European issues and samples, and for the distribution of sample countries, found no passage establishing where the large majority of research was focused. (LLM, conf=0.70)

  cites Kubin & von Sikorski 2021 sourceExperimental — accuracy not yet measured

In the paper

“This suggests that peer influence may be effective in shaping norms in social media environments when the peers are credible members of one's in-group (Paluck & Green 2009, Paluck et al. 2021).”

What the sources say

• ?Not checked — no full text of the sourcecites Paluck & Green 2009 source
• Supported

  The ‘Normative Interventions in Social Media Platforms’ section reports that an in-group Twitter user with many followers reduced harassment and concludes that norm enforcement can be influential when the messenger is a credible in-group member. The paper notes that the effect of a single intervention faded over time; the claim’s ‘may be effective’ wording is consistent with that limitation. No page number is supplied in the passages. (LLM, conf=0.93)

  cites Paluck et al. 2021 source

In the paper

“For instance, 86% of the research on social media and polarization is from the United States (Kubin & von Sikorski 2021).”

What the sources say

• ?Could not verify

  The available Results passage lists a “Country of sample” section but contains no findings or percentages. Searches for “86%” and the share of studies using U.S. samples returned no passage establishing the claimed figure; the available copy appears to contain headings and links rather than the relevant body text. (LLM, conf=0.72)

  cites Kubin & von Sikorski 2021 sourceExperimental — accuracy not yet measured

In the paper

“For instance, identity-and empathy-based bystander interventions on social media can effectively reduce incivility (Munger 2020), hate speech (Hangartner et al. 2021, Munger 2017, Siegel & Badaan 2020), and misinformation (Pretus et al. 2022).”

What the sources say

• ?Not checked — no full text of the sourcecites Munger 2020 source
• Supported

  The citation to Hangartner et al. supports the hate-speech portion of the sentence, not the separately cited claims about incivility or misinformation. The Abstract reports that empathy-based replies reduced subsequent xenophobic hate speech among Twitter users; the Discussion describes the effect as relatively small. This paper does not test an identity-based intervention, but it supports the empathy-based example within the cited group. (LLM, conf=0.92)

  cites Hangartner et al. 2021 source
• ?Not checked — no full text of the sourcecites Munger 2017 source

In the paper

“People across the political spectrum believe that misinformation and hate speech should be restricted based on severity, regardless of the target or topic (Kozyreva et al. 2023, Rasmussen 2022, Rathje et al. 2023).”

What the sources say

• Partly supported

  The Discussion reports that US respondents were more willing to restrict misinformation as the severity of its consequences increased, and that the account holder’s characteristics had little effect. But it explicitly says the misinformation topic mattered, with climate-change denial acted on less often than Holocaust or election denial. This paper studies misinformation moderation, not hate-speech restrictions or whether the target of hate speech affects decisions. (LLM, conf=0.90)

  cites Kozyreva et al. 2023 sourceExperimental — accuracy not yet measured
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Rasmussen 2022
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Rathje et al. 2023

In the paper

“In general, people on the political left are more supportive of regulating social media platforms (Kozyreva et al. 2023, Rasmussen 2022), reflecting liberals' general tendency to be more supportive, and conservatives' tendency to more opposing, of regulatory policies (e.g., Grossman & Hopkins 2016).”

What the sources say

• Partly supported

  The Discussion reports that Democrats preferred preventing dangerous falsehoods across four content-moderation scenarios, while Republicans preferred free speech and imposed fewer restrictions. That supports a partisan difference in attitudes toward moderating online misinformation, but the paper limits its conclusions to US respondents and does not establish a general preference for regulating social media platforms across issues. (LLM, conf=0.84)

  cites Kozyreva et al. 2023 sourceExperimental — accuracy not yet measured
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Rasmussen 2022

In the paper

“The relational mobility afforded by social media ensures that even those who burn bridges with their original social groups can find new groups that agree with their extreme opinions.”

In the paper

“The design and incentives of social media accelerate moral content.”

In the paper

“while also potentially amplifying more constructive facets of morality, such as social support, prosociality, and collective action”

• Also stated in: § INTRODUCTION · plain

  “as well as some positive aspects of morality, such as social support, prosociality, and collective action.”

In the paper

“moral outrage can encourage an active response, such as protests for social justice (Hutcherson & Gross 2011, Jost et al. 2018, Spring et al. 2018, van Zomeren et al. 2004)”

What the sources say

• ?Not checked — no full text of the sourcecites Hutcherson & Gross 2011 source
• ?Not checked — no full text of the sourcecites Jost et al. 2018 source
• ?Not checked — no full text of the sourcecites Spring et al. 2018 source

In the paper

“social media makes moral behavior (such as punishment) less costly”

• Also stated in: § Abstract · plain

  “social media makes moral behavior (such as punishment) less costly.”

In the paper

“One means by which individuals and groups can capture attention and drive engagement on these platforms is by sharing morally and emotionally evocative content”

• Also stated in: § INTRODUCTION · plain

  “One means by which individuals can capture attention and drive engagement is by sharing morally and emotionally evocative content (see Brady et al. 2020a,b).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brady et al. 2020a,b

In the paper

“people tend to misinterpret social media posts as expressing greater outrage than the author actually feels (Brady et al. 2023)”

What the sources say

• ?Not checked — no full text of the sourcecites Brady et al. 2023 source

In the paper

“social media often acts as an accelerant for existing moral dynamics, amplifying outrage, status seeking, and intergroup conflict”

• Also stated in: § INTRODUCTION · hedged

  “Our review of the literature suggests that social media often acts like an accelerant for existing moral dynamics-amplifying negative facets of morality such as outrage, harassment, status seeking, and intergroup conflict”

In the paper

“social media offers high-visibility and low-cost forms of engagement, such as comments and likes, which make it easy for users to punish, shame, and pile on transgressors”

In the paper

“Social media algorithms further accelerate this cycle of outrage by promoting related ideological content.”

In the paper

“Moral content often goes viral on social media”

In the paper

“This feedback can then serve as a type of reinforcement learning that further fuels outrage (Brady et al. 2021)”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brady et al. 2021

In the paper

“The anonymity of social media may also embolden some people to express views and emotions they may not disclose in face-to-face interactions (Nitschinsk et al. 2022, Zimmerman & Ybarra 2016)”

What the sources say

• ?Not checked — no full text of the sourcecites Nitschinsk et al. 2022 source
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Zimmerman & Ybarra 2016

In the paper

“social media reproduces-and often exaggerates-the social behavior and intergroup dynamics that emerge from our group identities, moral sensibilities, and political polarization”

In the paper

“social media can amplify norm following and enforcement at a speed and scale that would be difficult to implement in the real world”

In the paper

“The larger the number of people who publicly criticize a moral transgression, the more likely third parties are to empathize with the original perpetrator of the transgression; this is known as”

What the sources say

• ?Not checked — no full text of the sourcecites Sawaoka & Monin 2018 source

In the paper

“each moral-emotional word added to a social media post is associated with 12% more retweets (Brady & Van Bavel 2021a)”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brady & Van Bavel 2021a

In the paper

“moral content captures attention (Brady et al. 2020b)”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brady et al. 2020b

In the paper

“In discussions with like-minded individuals, people can be persuaded to adopt more extreme ideological positions, leaving an interaction with more polarized views than they initially had (Mackie & Cooper 1984, Moscovici & Zavalloni 1969).”

What the sources say

• ?Not checked — no full text of the sourcecites Mackie & Cooper 1984 source
• ?Not checked — no full text of the sourcecites Moscovici & Zavalloni 1969 source

In the paper

“Extremists' participation online may have a polarizing effect on peoples' more moderate ideological views.”

In the paper

“Social media might also cause people to encounter more divisive and polarizing content than they actually want to see.”

In the paper

“People also tend to overestimate the degree of polarization (Levendusky & Malhotra 2016, Westfall et al. 2015) and animosity (Mernyk et al. 2022, Ruggeri et al. 2021) between political groups, which may be exacerbated by the abundance of divisive content they see online.”

In the paper

“In other words, extremists' contribution on social media may inaccurately depict political groups as more polarized than they truly are (known as false polarization), yet their participation may lead to real ramifications in which they convince others of their extreme views.”

In the paper

“This push toward extremist views may also result in social media acting as a catalyst for conspiratorial thinking.”

In the paper

“The result is massive rallies that emerge on the streets overnight but often fizzle just as quickly (Fisher 2022a).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Fisher 2022a

In the paper

“A meta-analysis of antisocial online behaviors found that psychopathy was the strongest and most consistent predictor of antisocial online behaviors, followed by Machiavellianism and everyday sadism (Moor & Anderson 2019)”

What the sources say

• ?Not checked — no full text of the sourcecites Moor & Anderson 2019 source

In the paper

“Political extremists, both liberal and conservative, show higher levels of outrage on social media compared to politically moderate users (Brady et al. 2021).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brady et al. 2021

In the paper

“Status seeking via outrage expression is effective because people often equate moral outrage expressions with the speaker's own morality (Skitka 2010, Tosi & Warmke 2016)”

What the sources say

• ?Not checked — no full text of the sourcecites Skitka 2010 source
• ?Not checked — no full text of the sourcecites Tosi & Warmke 2016 source

In the paper

“This lack of gatekeepers can facilitate organizing and collective action (Spring et al. 2018).”

What the sources say

• ?Not checked — no full text of the sourcecites Spring et al. 2018 source

In the paper

“In fact, heavy social media users are prone to false consensus effects, meaning they overestimate how widely held their views are (Bunker & Varnum 2021).”

What the sources say

• ?Not checked — no full text of the sourcecites Bunker & Varnum 2021 source

In the paper

“For example, social media might be making nonviolent protests less effective because they are easier to organize without leadership, which makes them less enduring.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Fisher 2022a

In the paper

“Social media use is associated with greater conspiratorial beliefs among people who are predisposed to conspiratorial thinking (Enders et al. 2023).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Enders et al. 2023

In the paper

“In other words, extremists' contribution on social media may inaccurately depict political groups as more polarized than they truly are (known as false polarization), yet their participation may lead to real ramifications in which they convince others of their extreme views.”

In the paper

“Open access to online platforms can be beneficial, enabling marginalized voices to face lower barriers to disseminate moral messages and find social support (Schmitz et al. 2022).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Schmitz et al. 2022

In the paper

“Anyone has the opportunity to create a social media account and post content that rapidly goes viral even if that content consists of baseless conspiracy theories or misinformation (Vosoughi et al. 2018).”

What the sources say

• ?Not checked — no full text of the sourcecites Vosoughi et al. 2018 source

In the paper

“This makes it extremely difficult to evaluate the net moral impact of social media on society (see Brady & Crockett 2019).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brady & Crockett 2019

In the paper

“Moral discourse online is dominated by ideological extremists.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brady et al. 2021

In the paper

“In other words, even though people engage with divisive content on social media-perhaps because it captures attention and drives engagement-this behavior does not align with people's stated preferences (see Figure 3).”

In the paper

“Extremists tend to be dogmatic and to present their beliefs as facts (Harris & Van Bavel 2020, Toner et al. 2013), and they may incite others to become more ideologically polarized.”

In the paper

“Moreover, the amount of moral convergence in online groups (e.g., people in a group sharing the same moral views) predicts radicalization (Atari et al. 2022), and, as we mentioned above, tweets containing moral-emotional language are more likely to receive hate speech in the replies (Solovev & Pröllochs 2023).”

What the sources say

• ?Not checked — no full text of the sourcecites Atari et al. 2022 source

In the paper

“Facebook were even more vaccine hesitant than those who got their news primarily from Fox News (Lazer et al. 2021).”

What the sources say

• ?Not checked — no full text of the sourcecites Lazer et al. 2021 source

In the paper

“Algorithms seem to prioritize the spread of information that is emotional, is polarizing, or captures our attention (Brady et al. 2020a,b).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Brady et al. 2020a,b

In the paper

“For instance, a full 23% of political images on Facebook contain misinformation (Yang et al. 2023).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Yang et al. 2023

In the paper

“One analysis found that COVID-19 rumors that contained moral-emotional language were more likely to spread widely on Twitter (Solovev & Pröllochs 2022).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Solovev & Pröllochs 2022

In the paper

“Moreover, moralized rhetoric online may spill over into real-world violence (Fisher 2022b, Mooijman et al. 2018).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Fisher 2022b
• ?Not checked — no full text of the sourcecites Mooijman et al. 2018 source

In the paper

“However, social media may have different effects on polarization in non-US contexts.”

In the paper

“Moreover, using moral-emotional rhetoric can trigger hate speech among recipients: Each additional moral word is associated with a 11-16% increase in eliciting hate speech from readers (Solovev & Pröllochs 2023).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Solovev & Pröllochs 2023

In the paper

“The increased spread of moralized content online may further fuel polarization and intergroup conflict.”

In the paper

“Social media may be responsible in part for this polarization around public health beliefs.”

In the paper

“For instance, Facebook was implicated in an outbreak of ethnic cleansing in Myanmar against the Rohingya (Fisher 2022b).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Fisher 2022b

In the paper

“Thus, algorithms that promote outrage may prioritize promoting false information and conspiracy theories.”

In the paper

“One study found that fact-checked false stories spread faster and farther than factchecked true stories on Twitter (Vosoughi et al. 2018).”

What the sources say

• ?Not checked — no full text of the sourcecites Vosoughi et al. 2018 source

In the paper

“Another analysis of Facebook and Twitter posts found that the misinformation containing moral outrage (as detected by a moral outrage machine-learning classifier) was more likely to spread than misinformation that did not contain moral outrage (McLoughlin et al. 2021).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites McLoughlin et al. 2021

In the paper

“However, new research suggests there is more consensus in public opinion on regulating social media than previously thought.”

In the paper

“Social media seems to amplify exposure to moral content and action.”

In the paper

“These false beliefs help explain why social media can fuel (moral) conflicts, as most people are more moderate than people think (Levendusky & Malhotra 2016) and consume news from the same sources on social media (Guess 2021), while those who engage on social media are the most engaged partisans (Settle 2018).”

In the paper

“This is despite the fact that 9 out of 10 countries with the highest numbers of Facebook users are located in the Global South (Ghai et al. 2022).”

What the sources say

• ?Not checked — no full text of the sourcecites Ghai et al. 2022 source

In the paper

“There is reason to believe that social media exacerbates these issues by disproportionately exposing people to extremists.”

In the paper

“In the political domain, there is ample evidence that affective polarization is on the rise (Finkel et al. 2020, Iyengar & Westwood 2015), leading to concerns about reduced support for democratic norms (Broockman et al. 2022, Kingzette et al. 2021).”

What the sources say

• ?Not checked — no full text of the sourcecites Finkel et al. 2020 source
• ?Not checked — no full text of the sourcecites Iyengar & Westwood 2015 source

In the paper

“One promising strategy is motivating bystanders to denounce hostility or harassment on social media (Munger 2017).”

What the sources say

• ?Not checked — no full text of the sourcecites Munger 2017 source

In the paper

“While most people are passive on social media and only consume content (Settle 2018), encouraging users to participate in online discourse and to react negatively to hostility may improve the social media environment.”

What the sources say

• ?Not checked — no full text of the sourcecites Settle 2018 source

In the paper

“While most people are passive on social media and only consume content (Settle 2018), encouraging users to participate in online discourse and to react negatively to hostility may improve the social media environment.”

In the paper

“As such, our ability to generalize across platforms is severely limited.”

In the paper

“Other experimental work has found that increasing people's motivation to be accurate, and reducing people's motivation to view content through a partisan lens, improves the accuracy of people's beliefs and sharing decisions (Rathje et al. 2022a).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Rathje et al. 2022a

In the paper

“However, these strategies often mitigate, rather than address, the root of the problem.”

In the paper

“Moreover, the amount of moral convergence in online groups (e.g., people in a group sharing the same moral views) predicts radicalization (Atari et al. 2022), and, as we mentioned above, tweets containing moral-emotional language are more likely to receive hate speech in the replies (Solovev & Pröllochs 2023).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Solovev & Pröllochs 2023

In the paper

“Therefore, our understanding of the consequences of moral discourse on social media may not accurately reflect the experience of users from other parts of the world or understudied communities.”

In the paper

“Thus, harnessing people's social identities or social norms can motivate prosocial behavior (Van Bavel & Packer 2021).”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Van Bavel & Packer 2021

In the paper

“As such, aspects of social media design, incentive structures, and algorithms can all be shifted to encourage people to share more positive content at scale.”