Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Open accessAbstract
How do people think about what is appropriate, allowed, required, or forbidden? Heyes’s “cognitive gadgets” account of norm psychology proposes that cultural selection affects not just the content of norms but also how people think and feel about norms in general. Contra nativist views that paint human normativity as genetically inherited and evolving at a glacial pace, Heyes’s model suggests that people alive today have substantially more control over how future generations think about norms and their enforcement. Here, we explore one important implication of Heyes’s account: New technologies, such as social media, can spur rapid cultural evolution of normativity (Acerbi, 2019). Commentary plays a key role in the cultural transmission of norms by defining the terms of compliance and enforcement, and it is increasingly taking place online, with more than 4 billion social media users worldwide (Dixon, 2022). Building on recent studies of online normative discourse, we speculate how three features of social media shape the cultural evolution of normativity: hidden incentives, multiple audiences, and speed of transmission. By incentivizing particular types of commentary over others in ways that are not always transparent to users, social media can teach people new ways to think and feel about norms. For example, preliminary evidence suggests that social media incentivizes moral outrage. Because social media platforms profit more by keeping users online, their algorithms promote content that is most likely to be shared. Users are especially likely to share commentary containing moralized and emotional language (e.g., moral outrage) because it attracts attention and highlights group identity (Brady, Crockett, & Van Bavel, 2020; Brady et al., 2017, 2019; Brady, Gantman, & Van Bavel, 2020; Brady & Van Bavel, 2021; Crockett, 2017), and algorithms amplify this tendency (Brady et al., in press; Chakradhar, 2021; Chowdhury, 2021; Huszár et al., 2022). The widespread sharing of moral outrage has two consequences: It teaches users that outrage expressions are normative, and it directly reinforces those outrage expressions. Thus, users learn over time to express more outrage (Brady et al., 2021), which further inflates beliefs that outrage is normative. Inflated prior beliefs about the prevalence of outrage may then lower the threshold for perceiving it, causing individuals to believe others are more outraged than they actually are (Brady et al., 2023). We speculate that these algorithmic social-learning processes could extend beyond outrage expressions to affect other types of normative thinking. For example, simplified moral narratives with a clear villain and victim may generate more engagement than more nuanced accounts. Because social media algorithms gamify engagement, individuals may learn over time to communicate and perhaps even to cognitively represent moral situations in ways that essentialize moral character, which in turn increases harsh punitive attitudes (Heiphetz, 2020). Moreover, there is evidence that social media algorithms disproportionately incentivize and spread right-wing over left-wing political commentary in the United States (Huszár et al., 2022). Such incentives, over time, could promote not just the content of right-wing political views but also right-wing styles of normative thinking, such as moral parochialism (Bai et al., 2021; Kahane et al., 2018; Waytz et al., 2019). Furthermore, because social media algorithms disproportionately incentivize criticism directed toward outgroups (Rathje et al., 2021), this could increase the impact of social identity on normative thinking, making people quicker to blame and assume the worst intentions of out-group members. Such a dynamic would 1187395 PPSXXX10.1177/17456916231187395Brady, CrockettPerspectives on Psychological Science research-article2023
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Written from the paper’s full text.
TL;DR
This commentary extends Heyes's "cognitive gadgets" account of norm psychology to argue that social media can drive rapid cultural evolution of how people think and feel about norms, not just the content of norms themselves. The authors speculate that three features of social media—hidden incentives, context collapse, and speed of transmission—reshape normative cognition, and they call for designing technologies that steer this evolution toward global cooperation.
Key findings
- The authors propose that social media's hidden incentives teach users new normative dispositions: because platforms profit from keeping users online, algorithms promote shareable content, and users are especially likely to share moralized, emotional language such as moral outrage. Widespread sharing of outrage teaches users that outrage is normative and directly reinforces outrage expression, so users learn to express more outrage over time, which further inflates beliefs that outrage is normative and can lower the threshold for perceiving it.
- They speculate these processes extend beyond outrage to other normative thinking—e.g., simplified villain/victim moral narratives may out-engage nuanced accounts, potentially essentializing moral character and increasing harsh punitive attitudes; evidence cited indicates algorithms disproportionately incentivize and spread right-wing over left-wing political commentary in the United States, and disproportionately incentivize criticism of outgroups, which could heighten moral parochialism and out-group blame.
- "Context collapse" (Marwick & Boyd, 2011) flattens multiple audiences into one, complicating reputation management because commentary meant for one audience may reach a very different one; some users develop strategies such as self-censorship, and as these strategies spread they may drive cultural evolution of more sophisticated reputation-management strategies optimized for digital spaces.
- Unprecedented transmission speed increases social learning: users can observe thousands of reactions and receive feedback from thousands of people within minutes. Viral outrage "pile-ons" increase beliefs that outrage is normative but also increase sympathy for the offender when outrage seems disproportionate; observing rapid norm change may foster cynical beliefs about moral expression or a "normative nihilism" that drives retreat to perceived-traditional norms.
Methods
- This is a conceptual commentary, not an empirical study; the authors explicitly "speculate" about how social media shapes the cultural evolution of normativity, building on Heyes's cognitive-gadgets account and on prior studies of online normative discourse.
- The argument is organized around three features of social media: hidden incentives, multiple audiences (context collapse), and speed of transmission.
- The text cites more than 4 billion social media users worldwide (Dixon, 2022) as context; no new data, sample, or statistical analysis is reported.
Limitations
- The paper states no formal limitations section; the authors repeatedly frame their claims as speculation ("we speculate," "could," "may"), and the proposed consequences for normative cognition are not tested here.
- Evident from the text: the argument is a theoretical synthesis relying on cited findings from other studies (e.g., outrage sharing, algorithmic amplification, context collapse), so the causal claims about social media reshaping norm psychology remain hypotheses rather than demonstrated effects.
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- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Commentary is increasingly taking place online.
“it is increasingly taking place online, with more than 4 billion social media users worldwide (Dixon, 2022).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Dixon, 2022
Not checked in the free run.
- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
New technologies, such as social media, can spur rapid cultural evolution of normativity.
“New technologies, such as social media, can spur rapid cultural evolution of normativity (Acerbi, 2019).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Acerbi, 2019
Not checked in the free run.
- Rests on an assumption: Heyes's cognitive gadgets account of norm psychology proposes that cultural selection affects not just the content of norms but also how people think and feel about norms in general.
- Rests on an assumption: Heyes's model suggests that people alive today have substantially more control over how future generations think about norms and their enforcement.
- Interpretationreasoning§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Widespread sharing of moral outrage directly reinforces those outrage expressions.
“and it directly reinforces those outrage expressions”
Quote in the paperSubstantial claim - Interpretationreasoning§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Widespread sharing of moral outrage teaches users that outrage expressions are normative.
“It teaches users that outrage expressions are normative”
Quote in the paperSubstantial claim - Interpretationreasoning§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Context collapse on social media substantially complicates reputation management because commentary meant for one particular audience might end up being seen by a very different audience.
“Context collapse on social media substantially complicates reputation management because commentary meant for one particular audience might end up being seen by a very different audience, perhaps even one that the commenter did not even know existed.”
Quote in the paperSubstantial claim
- Interpretationreasoning§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Social media can teach people new ways to think and feel about norms by incentivizing particular types of commentary over others in ways that are not always transparent to users.
“By incentivizing particular types of commentary over others in ways that are not always transparent to users, social media can teach people new ways to think and feel about norms.”
Quote in the paperSubstantial claim- Rests on an assumption: Social media platforms profit more by keeping users online.
- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Preliminary evidence suggests that social media incentivizes moral outrage.
“For example, preliminary evidence suggests that social media incentivizes moral outrage.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Brady, Crockett, & Van Bavel, 2020
Not checked in the free run.
- cites Brady et al., 2017
Not checked in the free run.
- cites Brady et al., 2019
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- Interpretationreasoning§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Commenters must hold very different conceptions of their imagined audience in mind when engaging in online commentary compared with offline conversations in which the audience is usually fully known.
“To navigate this, commenters must hold very different conceptions of their imagined audience in mind when engaging in online commentary compared with offline conversations in which the audience is usually fully known.”
Quote in the paperSubstantial claim - Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
At least some social media users develop strategies to deal with context collapse, such as self-censorship.
“There is evidence that at least some social media users develop strategies to deal with context collapse, such as self-censorship (Marwick & Boyd, 2011).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Marwick & Boyd, 2011
Not checked in the free run.
- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Users learn over time to express more outrage.
“Thus, users learn over time to express more outrage (Brady et al., 2021)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Brady et al., 2021
Not checked in the free run.
- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Users are especially likely to share commentary containing moralized and emotional language because it attracts attention and highlights group identity.
“Users are especially likely to share commentary containing moralized and emotional language (e.g., moral outrage) because it attracts attention and highlights group identity”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Brady, Crockett, & Van Bavel, 2020
Not checked in the free run.
- cites Brady et al., 2017
Not checked in the free run.
- cites Brady et al., 2019
Not checked in the free run.
- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
A second consequential feature of social media is the way it flattens multiple audiences into one, a phenomenon known as context collapse.
“A second consequential feature of social media is the way it flattens multiple audiences into one, a phenomenon known as”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Marwick & Boyd, 2011
Not checked in the free run.
- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Social media algorithms disproportionately incentivize and spread right-wing over left-wing political commentary in the United States.
“Moreover, there is evidence that social media algorithms disproportionately incentivize and spread right-wing over left-wing political commentary in the United States (Huszár et al., 2022).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Huszár et al., 2022
Not checked in the free run.
- Interpretationreasoning§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Social media design is not currently optimized for cultural selection of gadgets that promote cooperation.
“social media design is not currently optimized for cultural selection of gadgets that promote cooperation”
Quote in the paperNot a substantial claim- Rests on an assumption: Social media platforms profit more by keeping users online.
- Rests on an assumption: On social media, information spreads through social networks at an unprecedented speed.
- Rests on an assumption: Users can observe thousands of social reactions to normative commentary every time they log on to social media and receive social feedback on their own commentary from thousands of people within minutes.
- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Inflated prior beliefs about the prevalence of outrage may lower the threshold for perceiving it, causing individuals to believe others are more outraged than they actually are.
“Inflated prior beliefs about the prevalence of outrage may then lower the threshold for perceiving it, causing individuals to believe others are more outraged than they actually are (Brady et al., 2023).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Brady et al., 2023
Not checked in the free run.
- Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Social media algorithms disproportionately incentivize criticism directed toward outgroups.
“Furthermore, because social media algorithms disproportionately incentivize criticism directed toward outgroups (Rathje et al., 2021)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Rathje et al., 2021
Not checked in the free run.
- Interpretationreasoning§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Information spreading through social networks at unprecedented speed can substantially increase the rate of social learning.
“which in turn can substantially increase the rate of social learning”
Quote in the paperNot a substantial claim- Rests on an assumption: On social media, information spreads through social networks at an unprecedented speed.
- Interpretationreasoning§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of Normativity
Expressing more outrage further inflates beliefs that outrage is normative.
“which further inflates beliefs that outrage is normative”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 1
- May combine two claims. 1
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of NormativityThere are more than 4 billion social media users worldwide.
“with more than 4 billion social media users worldwide (Dixon, 2022).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Dixon, 2022
Not checked in the free run.
May combine two claims.
Premisecitation§ Norm Psychology in the Digital Age: How Social Media Shapes the Cultural Evolution of NormativityViral outrage pile-ons increase beliefs that outrage is normative but also increase sympathy for the offender because the outrage is seen as disproportionate to the offense.
“For example, viral outrage”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Sawaoka & Monin, 2018
Not checked in the free run.
The paper relies on this without support.
Commentary plays a key role in the cultural transmission of norms by defining the terms of compliance and enforcement.
“Commentary plays a key role in the cultural transmission of norms by defining the terms of compliance and enforcement”
The paper relies on this without support.
Social media platforms profit more by keeping users online.
“Because social media platforms profit more by keeping users online”
The paper relies on this without support.
On social media, information spreads through social networks at an unprecedented speed.
“On social media, information spreads through social networks at an unprecedented speed”
The paper relies on this without support.
Users can observe thousands of social reactions to normative commentary every time they log on to social media and receive social feedback on their own commentary from thousands of people within minutes.
“Users can observe thousands of social reactions to normative commentary every time they log on to social media and receive social feedback on their own commentary from thousands of people within minutes.”
The paper relies on this without support.
Heyes's cognitive gadgets account of norm psychology proposes that cultural selection affects not just the content of norms but also how people think and feel about norms in general.
“Heyes's”
The paper relies on this without support.
Heyes's model suggests that people alive today have substantially more control over how future generations think about norms and their enforcement.
“Contra nativist views that paint human normativity as genetically inherited and evolving at a glacial pace, Heyes's model suggests that people alive today have substantially more control over how future generations think about norms and their enforcement.”
The paper relies on this without support.
The cognitive-gadgets account suggests that people's norm psychology can change on a much more rapid timescale.
“The cognitive-gadgets account is more optimistic: It suggests that people's norm psychology can change on a much more rapid timescale”
The paper relies on this without support.
The cognitive-gadgets account suggests that people have much more agency and control over how that change proceeds.
“and that people have much more agency and control over how that change proceeds.”
Claims other papers make about this one
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Algorithmic amplification of emotionally and morally charged content may feed back into human social learning-for instance, inflating beliefs about the normative value of expressing moral outrage, increasing outgroup animosity or creating echo chambers and filter bubbles.
“The algorithmic amplification of such content may then feed back into human social learning-for instance, inflating beliefs about the normative value of expressing moral outrage 138,139 , increasing outgroup animosity 140 or creating echo chambers and filter bubbles [141][142][143] .”
From Machine culture (2023) · cites this paper as [140]
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- Authors
- Brady, W. J., & Crockett, M. J.
- Affiliations
- Northwestern University (US)
- Princeton University (US)
- Corresponding author
- Crockett, M. J.
- Venue
- Perspectives on Psychological Science
- Publisher
- SAGE Publications
- Published
- 2023-07-31
- Volume
- 19
- Issue
- 1
- Pages
- 62-64
- ISSN
- 1745-6916 (ISSN-L)
- 1745-6924
- OpenAlex
- W4385406846
- Semantic Scholar
- 230e81b38ca0a844ecc2a1f52926c2b4d37a82e2
- Cited by
- 26
- References
- 25
- Citations by year
- 2026: 9 · 2025: 6 · 2024: 6 · 2023: 5
- FWCI
- 7.68
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Perspectives on Psychological Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- John Templeton Foundation (#61495 & #62816)
- Democracy Fund (R-201809-03031)
- Topics
- Social Sciences › Psychology › Social Psychology › Cultural Differences and Values
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Evolutionary Psychology and Human Behavior
- Social Sciences › Psychology › Social Psychology › Social Representations and Identity
- Keywords
- social media, cultural evolution, normativity, social norms, digital technologies
- MeSH terms
- Cultural Evolution, Humans, Social Behavior, Social Media, Social Norms
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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