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PNAS Nexus, 2024, 3, pgae286
https://doi.org/10.1093/pnasnexus/pgae286
Advance access publication 15 October 2024
Perspective
Explanations of and interventions against affective
polarization cannot afford to ignore the power of ingroup
norm perception
Zi Ting You
a
and Spike W. S. Lee
a,b,
*
a
Department of Psychology, University of Toronto, 100 St. George Street, Toronto, Ontario M5S 3G3, Canada
b
Rotman School of Management, University of Toronto, 105 St. George Street, Toronto, Ontario M5S 3E6, Canada
*To whom correspondence should be addressed: Email: spike.lee@utoronto.ca
Edited By: Eugen Dimant
Abstract
Affective polarization, or animosity toward opposing political groups, is a fundamentally intergroup phenomenon. Yet, prevailing
explanations of it and interventions against it have overlooked the power of ingroup norm perception. To illustrate this power, we
begin with evidence from 3 studies which reveal that partisans’ perception of their ingroup’s norm of negative attitudes toward the
outgroup is exaggerated and uniquely predicts their own polarization-related attitudes. Specically, our original data show that in
predicting affective polarization (i.e. how one feels about one’s partisan outgroup), the variance explained by ingroup norm
perception is 8.4 times the variance explained by outgroup meta-perception. Our reanalysis of existing data shows that in predicting
support for partisan violence (i.e. how strongly one endorses and is willing to engage in partisan violence), ingroup norm perception
explains 52% of the variance, whereas outgroup meta-perception explains 0%. Our pilot experiment shows that correcting ingroup
norm perception can reduce affective polarization. We elucidate the theoretical underpinnings of the unique psychological power of
ingroup norm perception and related ingroup processes. Building on these empirical and theoretical analyses, we propose approaches
to designing and evaluating interventions that leverage ingroup norm perception to curb affective polarization. We specify critical
boundary conditions that deserve prioritized attention in future intervention research. In sum, scientists and practitioners cannot
afford to ignore the power of ingroup norm perception in explaining and curbing affective polarization.
Keywords: affect, polarization, intergroup relations, norm perception, meta-perception
Competing Interest: The authors declare no competing interests.
Received: April 3, 2024. Accepted: June 30, 2024
© The Author(s) 2024. Published by Oxford University Press on behalf of National Academy of Sciences. This is an Open Access article
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Introduction
Our political climate today is fraught with toxic elements (1). One
of the most potent toxins is affective polarization—partisans’ ani-
mosity toward the opposing party’s supporters (2). Such animosity
exacerbates ideological polarization (3) and worsens behavioral
dynamics across the aisle (4). Scholars have suggested that build-
ing connections between partisans might ameliorate affective po-
larization (2, 5). Unfortunately, in real life, affectively polarized
partisans are not particularly motivated to build connections
with each other. If anything, they are highly motivated to avoid in-
teracting with those on the other side (6–10). With these social
forces at work, how can researchers intervene?
We argue that affective polarization, as a partisan phenom-
enon, is fundamentally rooted in intergroup relations and social
identity processes (11–14). To maximize the effectiveness of inter-
ventions, social and behavioral scientists must have a precise
understanding of the most powerful drivers of affective polariza-
tion. That is, we must identify which aspects of intergroup rela-
tions and social identity exert the strongest inuence. The goal
of this Perspective piece is to point out that prevailing
explanations of and interventions against affective polarization
have missed the mark. Specically, they have overlooked the
power of ingroup norm perception.
Our perspective is motivated by evidence and theory. In the
sections that follow, we begin with evidence from 3 studies
(Section 1), all of which pit the effect of ingroup norm perception
(i.e. perception of one’s partisan ingroup members’ thoughts and
feelings) against that of outgroup meta-perception (i.e. perception
of one’s partisan outgroup members’ thoughts and feelings). One
study shows that in predicting affective polarization (i.e. how one
feels about one’s partisan outgroup), the variance explained by in-
group norm perception is 8.4 times the variance explained by out-
group meta-perception. Reanalysis of existing data shows that in
predicting support for partisan violence (SPV) (i.e. how strongly
one endorses and is willing to engage in partisan violence), in-
group norm perception explains 52% of the variance, whereas out-
group meta-perception explains 0%. A pilot experiment shows
that correcting ingroup norm perception reduces Republicans’ af-
fective polarization, whereas correcting outgroup meta-
perception does not.
To make sense of such evidence, we elucidate the theoretical
underpinnings of the unique psychological power of ingroup
norm perception and related ingroup processes (Section 2).
Building on these empirical and theoretical analyses, we propose
approaches to designing and evaluating interventions that lever-
age ingroup norm perception to curb affective polarization
(Section 3). Our proposed approaches are inspired by various ef-
fective interventions that have leveraged intergroup processes
(but not ingroup norm perception) to curb affective polarization
or those that have leveraged ingroup norm perception to change
diverse attitudinal and behavioral outcomes (but not affective po-
larization). We specify critical boundary conditions, derived from
theoretical principles, that deserve prioritized attention in future
intervention research.
Ingroup norm perception trumps outgroup
meta-perception in driving affective
polarization
Affective polarization is a phenomenon that involves group-level
psychological processes, not just individual-level ones. Partisans
dislike members of the opposing party often because of their party
afliation more than because of their individual characteristics
(15). Highlighting the “groupiness” of partisan dynamics, we bring
insights from intergroup relations and social identity theory (11)
to bear on our analysis of affective polarization. From the inter-
group literature, what processes exert robust psychological and
behavioral inuence?
Classic intergroup research (16) has found that simple group
categorization—seeing other individuals as either “us” (ingroup)
or “them” (outgroup)—is sufcient to cement bias toward the out-
group. This characterizes the reality of current political group re-
lations (13, 15). Partisans value being part of a group of politically
similar others. They dene part of their self-identity by their
membership in and belongingness to their political ingroup.
Those outside this group, or politically dissimilar others, are out-
group members and targets of bias.
In the bipartisan context of the United States, one’s political in-
group vs. outgroup typically comprises those who support the
same vs. opposing political party. With only 2 major parties, group
categorization is particularly straightforward, salient, and easy.
For instance, partisans can discern even from still photos whether
a target is more likely a Democrat or Republican (17, 18). Easy
group categorization, unfortunately, comes with difcult inter-
group relations. With only 2 major parties, political group rela-
tions are prone to being construed as a zero-sum competition
because “their win equals our loss” (19), resulting in hypersensitiv-
ity to the relative successes of one’s political ingroup vs. outgroup.
These dynamics of American politics bring group membership
to the forefront. When ingroup identities and fellow ingroup
members are highly valued (20), psychological processes related
to the ingroup exert powerful inuence on how people think,
feel, and act toward outgroup members (21). For example, individ-
uals tend to assimilate to what they perceive to be their ingroup
members’ normative attitudes and behaviors. Throughout this
paper, by “normative,” we mean descriptive norms (“what others
do”; as opposed to “what should be done,” which would be injunct-
ive norms) (22, 23). We contend that these processes are especially
relevant to political group dynamics.
Given the well-established impact of ingroup processes, one
might expect their role to be prominently featured in psychologic-
al research on affective polarization. That is not the case.
Psychological research on affective polarization has largely
ignored the power of individuals’ perception of their ingroup’s at-
titudes toward the outgroup, despite how strongly the ingroup g-
ures into individuals’ social identity. To be clear, existing
explanations of affective polarization have drawn on intergroup
processes in general, but have not incorporated how individuals
adopt their ingroup members’ attitudes in particular.
Consider a recent popular paradigm in this area of research: out-
group meta-perception. It focuses on one’s perception of the parti-
san outgroup’s attitudes toward one’s partisan ingroup (24, 25).
Outgroup meta-perception has several properties. First, it tends to
be negatively exaggerated, i.e. people tend to have an exaggerated
perception of how negatively their outgroup feels toward their in-
group. Second, negatively exaggerated outgroup meta-perception
tends to worsen people’s feelings toward the outgroup. Third, pre-
senting accurate information to correct exaggerated outgroup
meta-perception tends to improve feelings toward the outgroup.
While these properties are valuable and have inspired our own
thinking, outgroup meta-perception is fundamentally different
from ingroup norm perception. The two kinds of perception imply
different roots of affective polarization and suggest different foci
of intervention. Explaining affective polarization in terms of out-
group meta-perception implies that affective polarization is par-
ticularly sensitive to intergroup dynamics and is reactive to one’s
perception of the outgroup’s attitudes (26). Explaining affective po-
larization in terms of ingroup norm perception implies that one’s
negativity toward the outgroup can emerge from dynamics within
one’s ingroup itself, without being a response to one’s perception
of the outgroup’s negativity toward one’s ingroup.
Juxtaposing ingroup norm perception and outgroup meta-
perception raises a simple empirical question: which one matters
more for affective polarization? To nd out, we rst analyze data
from 2 studies that measure both ingroup norm perception and
outgroup meta-perception within each participant and thus allow
us to compare their unique predictive effects on polarization-
related outcomes.
Our original data
We collected and analyzed original data from U.S. partisans (123
Democrats, 114 Republicans, N = 237, attaining 87.46% statistical
power in detecting an effect size of Cohen’s f
2
= 0.05 at α = 0.05
with 2 predictors in the regression model) (see Supplementary
Materials and Methods for sample characteristics). Using the feel-
ings thermometer, participants rated how positive and warm they
felt toward various social groups, including Democrats and
Republicans (among others), from 0 = very cold to 100 = very
warm. Participants also rated how they perceived the average
Democrat and the average Republican to feel toward the same so-
cial groups, using the same feelings thermometer.
Altogether these ratings allowed us to assess 3 constructs of fo-
cal interest on the same metric: (i) each participant’s own feeling
toward their partisan outgroup, (ii) their ingroup norm perception
(i.e. perception of their partisan ingroup’s feeling toward their par-
tisan outgroup), and (iii) their outgroup meta-perception (i.e. per-
ception of their partisan outgroup’s feeling toward their partisan
ingroup). Descriptive statistics are provided in Table S1 and zero-
order correlations in Table S2.
Did ingroup norm perception and outgroup meta-perception
predict participants’ actual feelings toward their partisan out-
group? If so, which one was a stronger predictor? We mean-
centered the variables and regressed actual feelings toward
one’s partisan outgroup on both ingroup norm perception and
outgroup meta-perception (Table 1, model 1), then added control
2 | PNAS Nexus, 2024, Vol. 3, No. 10
predictors (model 2) including partisan afliation, its interaction
with ingroup norm perception, and its interaction with outgroup
meta-perception.
In model 1, actual feeling toward one’s partisan outgroup was
signicantly predicted by ingroup norm perception (β = 0.45,
P < 0.001; all regression coefcients reported in text are standar-
dized) and outgroup meta-perception (β = 0.16, P = 0.021).
However, the coefcient for ingroup norm perception was signi-
cantly larger than the coefcient for outgroup meta-perception,
F
1, 234
= 6.07, P = 0.015. The variance explained by ingroup norm
perception (13.24%) was 8.4 times the variance explained by out-
group meta-perception (1.58%).
After adding control predictors (model 2), actual feeling toward
one’s partisan outgroup remained predicted by ingroup norm
perception (β = 0.45, P < 0.001) and outgroup meta-perception
(β = 0.15, P = 0.027) in the same way as in model 1. These effects
were comparable (i.e. did not differ signicantly) between Demo-
crat and Republican participants (ingroup norm perception ×
partisan afliation, β = 0.01, P = 0.858; outgroup meta-perception ×
partisan afliation, β = −0.03 P = 0.609). There was a mean-level par-
tisan difference such that Republican participants felt warmer
toward Democrats than vice versa (main effect of partisan afli-
ation, β = 0.14, P = 0.010). But as far as our primary interest in the
predictive effects of ingroup norm perception and outgroup meta-
perception is concerned, actual feeling toward one’s partisan out-
group was predicted most strongly by ingroup norm perception
among both Democrats and Republicans.
To check for robustness, we conducted the same regression
analyses using a more complex operationalization of the 3 con-
structs—as difference scores—in accordance with existing research
on affective polarization (27). Specically, we operationalized (i)
out-partisan feeling as one’s own feeling toward one’s partisan out-
group minus one’s own feeling toward one’s partisan ingroup, (ii)
ingroup norm perception as perception of one’s partisan ingroup’s
feeling toward one’s partisan outgroup minus perception of one’s
partisan ingroup’s feeling toward one’s partisan ingroup, and
(iii) outgroup meta-perception as perception of one’s partisan
outgroup’s feeling toward one’s partisan ingroup minus perception
of one’s partisan outgroup’s feeling toward one’s partisan outgroup.
Descriptive statistics are provided in Table S1, zero-order correla-
tions in Table S2, and regression results in Table S3. Actual differen-
tial feeling toward one’s partisan outgroup (over one’s partisan’s
ingroup) was signicantly predicted by ingroup norm perception
(β = 0.30, P < 0.001 without control predictors; β = 0.31, P < 0.001
with control predictors), not by outgroup meta-perception (β =
0.09, P = 0.222 without control predictors; β = 0.08, P = 0.321 with
control predictors).
Overall, our original data showed that ingroup norm perception
had strong and robust predictive effects on actual feelings toward
partisan outgroup members, whereas outgroup meta-perception
had weaker and less robust predictive effects. These patterns
emerged among both Democrats and Republicans. Collinearity
diagnostics (Table S4) found no concern of multicollinearity (28,
29). As a reality check, additional analyses (Supplementary
Results) conrmed that both Democrats and Republicans showed
affective polarization (i.e. feeling cold toward the partisan out-
group), negatively exaggerated ingroup norm perception (i.e. per-
ceiving their partisan ingroup’s feelings toward the partisan
outgroup to be worse than reality), and negatively exaggerated
outgroup meta-perception (i.e. perceiving their partisan out-
group’s feelings toward the partisan ingroup to be worse than
reality). Even though both ingroup norm perception and outgroup
meta-perception were negatively exaggerated, when pitted
against each other, it was ingroup norm perception that showed
much stronger predictive effects.
Our reanalysis of existing data
To assess the replicability of our ndings, we looked for additional
data from existing studies that would allow us to pit the predictive
effects of ingroup norm perception and outgroup meta-perception
against each other in a within-participant design. We found one
study: a 2022 PNAS paper by Mernyk et al. (30), whose study 1
met our criterion, with publicly available data (31).
The original authors focused on examining the effect of out-
group meta-perception on SPV. They hypothesized that partici-
pants’ own SPV toward their political outgroup was a response
to exaggerated meta-perception of their political outgroup’s SPV
toward their political ingroup. The original authors also measured
ingroup norm perception of SPV but did not compare its effect
against that of outgroup meta-perception on participants’ own
SPV. We reanalyzed their data to test this comparison.
Before presenting the results, we should note that SPV toward
one’s partisan outgroup is more severe than just feeling cold to-
ward them. It is plausible that the two might show different pat-
terns of results. For example, even if a Democrat felt cold
toward Republicans, they might, due to social desirability con-
cerns, be uncomfortable explicitly endorsing SPV statements
such as “it is justied for Democrats to use violence in advancing
their political goals these days” and “[it is] OK for an ordinary
Democrat in the public to harass an ordinary Republican on the
internet, in a way that makes the target feel frightened.” Our re-
analysis of Mernyk et al.’s (30) data explored whether SPV toward
one’s partisan outgroup was predicted by ingroup norm percep-
tion and outgroup meta-perception in the same way that cold feel-
ings toward one’s partisan outgroup was predicted by ingroup
norm perception and outgroup meta-perception in our original
data.
We applied the same lters and attention checks as in the ori-
ginal authors’ analyses, resulting in 702 participants (354
Democrats, 348 Republicans) (see Supplementary Materials and
Methods for sample characteristics). The sample size would attain
99.98% statistical power in detecting an effect size of Cohen’s
f
2
= 0.05 at α = 0.05 with 2 predictors in the regression model.
Descriptive statistics of the 3 constructs of focal interest are pro-
vided in Table S5 and zero-order correlations in Table S6.
Similar to our original study, reality checks (Supplementary
Results) conrmed that both ingroup norm perception of SPV
and outgroup meta-perception of SPV were exaggerated (i.e. per-
ceptions were graver than reality). Ingroup norm perception was
less exaggerated, or more accurate, than outgroup meta-
perception. This particular point led the original authors to offer
a suggestion that we consider understandable but a missed oppor-
tunity. They suggested that the higher accuracy of ingroup norm
perception “leaves little room for a correction intervention” (30).
Perhaps because of that, they did not explore the predictive effect
of ingroup norm perception any further, although the analytic
code provided in their online Supplementary Material included a
t test showing that ingroup norm perception of SPV was stronger
than actual SPV. We reran their code and reproduced what they
found (Supplementary Results). It suggested that ingroup norm
perception, while more accurate than outgroup meta-perception,
still exaggerated partisans’ actual SPV.
Recognizing the slightly exaggerated ingroup norm percep-
tion and more exaggerated outgroup meta-perception of SPV,
did both kinds of perception predict participants’ actual SPV
toward their partisan outgroup? We mean-centered the
You and Lee | 3
variables and regressed actual SPV toward one’s partisan out-
group on both ingroup norm perception and outgroup meta-
perception (Table 2, model 3), then added control predictors
(model 4) including partisan afliation, its interaction with in-
group norm perception, and its interaction with outgroup
meta-perception.
In model 3, actual SPV toward one’s partisan outgroup was sig-
nicantly predicted by ingroup norm perception (β = 0.74, P <
0.001) but not by outgroup meta-perception (β = 0.00, P = 0.947).
The coefcient for ingroup norm perception was signicantly
larger than the coefcient for outgroup meta-perception, F
1,
699
= 330.84, P < 0.001. The variance explained by ingroup norm
perception was 52.22%; the variance explained by outgroup meta-
perception was 0%.
The strong predictive effect of ingroup norm perception was ro-
bust to the addition of control predictors, as shown in model 4,
in which actual SPV toward one’s partisan outgroup remained
signicantly predicted by ingroup norm perception (β = 0.74,
P < 0.001) but not by outgroup meta-perception (β = 0.01, P = 0.857).
These effects were comparable (i.e. did not differ signicantly) be-
tween Democrat and Republican participants (ingroup norm
perception × partisan afliation, β = 0.00, P = 0.986; outgroup
meta-perception × partisan afliation, β = −0.03, P = 0.197). Mean
levels of actual SPV toward one’s partisan outgroup were compar-
able between Democrat and Republican participants (main effect
of partisan afliation, β = −0.01, P = 0.799). Collinearity diagnostics
(Table S4) again found no concern of multicollinearity (28, 29).
These results suggest that among both Democrats and
Republicans, actual SPV toward one’s partisan outgroup was
similar in level and similarly predicted by ingroup norm percep-
tion, not by outgroup meta-perception.
The cross-sectional and correlational nature of the two studies
analyzed here provide convergent evidence for the strong predict-
ive effect of ingroup norm perception. But neither study manipu-
lated it to test its causal effect. It is possible that partisans adjust
their perceived ingroup norm to match their own attitudes (in-
stead of basing their own attitudes on their perceived ingroup
norm), a process that Mernyk et al. (30) also suggested as a pos-
sible explanation for the correlation between partisans’ ingroup
norm perception of SPV and their own SPV. To provide causal evi-
dence, we conducted a pilot experiment.
Our pilot experiment
To examine the causal effects of ingroup norm perception and
outgroup meta-perception, we conducted a pilot experiment us-
ing a 2 (correcting vs. not correcting ingroup norm perception) ×
2 (correcting vs. not correcting outgroup meta-perception)
between-participant design. We collected and analyzed data
from U.S. partisans (216 Democrats, 216 Republicans, N = 432)
(see Supplementary Materials and Methods for sample
characteristics).
Using the feelings thermometer, participants rated how posi-
tive and warm they perceived the average Democrat and the aver-
age Republican to feel toward various social groups, including
Democrats and Republicans (ingroup norm perception and out-
group meta-perception) among other groups. Next, depending
on the condition, participants were presented with either correct
Table 1. Linear multiple regression models for our original data.
Predictor Model 1 Model 2
β (SE) 95% CI B (SE) Pβ (SE) 95% CI B (SE) P
Intercept 0.00 (0.05) −0.11 to 011 29.73 (1.50) <0.001 0.00 (0.05) −0.10 to 011 29.93 (1.49) <0.001
Ingroup norm perception 0.45
a
(0.07) 0.32 to 058
a
0.66
a
(0.10) <0.001
a
0.45 (0.07) 0.32 to 058
a
0.66
a
(0.10) <0.001
a
Outgroup meta-perception 0.16
a
(0.07) 0.02 to 029
a
0.23
a
(0.10) 0.021
a
0.15
a
(0.07) 0.02 to 028
a
0.22
a
(0.10) 0.027
a
Partisanship (−1 = Democrat, 1 =
Republican)
0.14
a
(0.05) 0.03 to 025
a
3.85
a
(1.49) 0.010
a
Ingroup norm perception × Partisanship 0.01 (0.07) −0.12 to 014 0.02 (0.10) 0.858
Outgroup meta-perception × Partisanship −0.03 (0.7) −0.17 to 010 −0.05 (0.10) 0.609
Observations | R
2
/Adjusted R
2
237 | 0.312/0.306 237 | 0.332/0.318
Cross-partisan feeling was regressed on ingroup norm perception and outgroup meta-perception (model 1), together with control predictors (model 2). Each kind of
perception was centered around its sample mean. Model comparison found that models 1 and 2 did not differ signicantly in variance explained, χ
2
3
= 2.33, P = 0.075.
Abbreviation: CI = condence interval.
a
Bold values indicate signicant predictors (other than intercept).
Table 2. Linear multiple regression models for our reanalysis of Mernyk et al. (30), study 1.
Model 3 Model 4
Predictor β (SE) 95% CI B (SE) Pβ (SE) 95% CI B (SE) P
Intercept 0.00 (0.03) −0.05 to 005 9.79 (0.50) <0.001 0.00 (0.03) −0.05 to 005 9.81 (0.50) <0.001
Ingroup norm perception 0.74
a
(0.03) 0.69 to 079
a
0.70
a
(0.02) <0.001
a
0.74
a
(0.03) 0.69 to 079
a
0.70
a
(0.03) <0.001
a
Outgroup meta-perception 0.00 (0.03) −0.05 to 005 0.00 (0.02) 0.947 0.01 (0.03) −0.05 to 006 0.00 (0.02) 0.857
Partisanship (−1 = Democrat, 1 =
Republican)
−0.01 (0.03) −0.06 to 004 −0.13 (0.50) 0.799
Ingroup norm perception × Partisanship 0.00 (0.03) −0.05 to 005 0.00 (0.03) 0.986
Outgroup meta-perception × Partisanship −0.03 (0.03) −0.09 to 002 −0.02 (0.02) 0.197
Observations | R
2
/Adjusted R
2
702 | 0.548/0.547 702 | 0.549/0.546
Support for political violence toward political outgroup was regressed on ingroup norm perception and outgroup meta-perception (model 3), together with control
predictors (model 4). Each kind of perception was centered around its sample mean. Model comparison found that models 3 and 4 did not differ signicantly in
variance explained, χ
2
3
= 0.61, P = 0.608.
Abbreviation: CI = condence interval.
a
Bold values indicate signicant predictors (other than intercept).
4 | PNAS Nexus, 2024, Vol. 3, No. 10
ingroup norm perception data from the original study described
previously, or correct outgroup meta-perception data from the
same study, or both, or neither. After the manipulation, partici-
pants rated how they felt toward these same groups (actual feel-
ings) among other variables. In accordance with existing
research on affective polarization (27) and our previous study
(Section 1a), we operationalized out-partisan feelings, ingroup
norm perception, and outgroup meta-perception as difference
scores. Descriptive statistics are provided in Table S7.
Correcting ingroup norm perception improved Republicans’ ac-
tual feeling toward their partisan outgroup (estimate = 20.52, SE =
7.92, t
424
= 2.59, P = 0.010). This effect remained signicant even
after controlling for premanipulation baseline levels of ingroup
norm perception and outgroup meta-perception (estimate =
17.86, SE = 6.76, t
416
= 2.64, P = 0.009). Correcting outgroup meta-
perception did not improve Republicans’ actual feeling toward
their partisan outgroup (estimate = 1.73, SE = 7.92, t
424
= 0.22,
P = 0.828).
Like Republicans, Democrats’ actual feeling toward their parti-
san outgroup was not signicantly affected by correcting out-
group meta-perception (estimate = −1.12, SE = 8.01, t
424
= −0.14,
P = 0.889). But unlike Republicans, Democrats’ actual feeling to-
ward their partisan outgroup was not signicantly affected by cor-
recting ingroup norm perception (estimate = −9.96, SE = 8.01, t
424
= −1.24, P = 0.214). This discrepancy between Republicans and
Democrats might have arisen because the corrective information
used in the ingroup norm perception manipulation was stronger
for Republicans than for Democrats: Republicans read that “ac-
tual Republicans felt between 36% to 51% warmer [toward
Democrats] than the average Republican’s guess,” whereas
Democrats read that “actual Democrats felt between 18% and
24% warmer [toward Republicans] than the average Democrat’s
guess.” This illustrates one of the challenges entailed by oper-
ationalizing the manipulation based on real data from prior stud-
ies, a theme we revisit in Section 3c.
Conceptually replicating the predictive effects in our original
data, across Republicans and Democrats, actual feeling toward
one’s partisan outgroup was signicantly predicted by baseline
levels of ingroup norm perception (β = 0.49, SE = 0.044, t
416
=
11.28, P < 0.001) and outgroup meta-perception (β = 0.090,
SE = 0.043, t
416
= 2.11, P = 0.036). Again, the coefcient for ingroup
norm perception was signicantly larger than the coefcient for
outgroup meta-perception, F
1, 416
= 31.61, P < 0.001. The variance
explained by ingroup norm perception (19.93%) was 28.5 times
the variance explained by outgroup meta-perception (0.70%).
In short, correcting ingroup norm perception improved
Republicans’ actual feeling toward their partisan outgroup.
Correcting outgroup meta-perception did not. Pitting baseline lev-
els of ingroup norm perception and outgroup meta-perception
against each other, both Republicans’ and Democrats’ actual
feeling toward their partisan outgroup was much more strongly
predicted by ingroup norm perception than by outgroup meta-
perception.
Summary of our original data, reanalysis
of existing data, and pilot experiment
To our knowledge, no existing work has specically examined in-
group norm perception as a driver of affective polarization,
let alone pitted it against outgroup meta-perception. Our original
data and our reanalysis of existing data converge in providing the
rst evidence that ingroup norm perception has unique, large, and
robust predictive effects on partisan animosity and support for
partisan violence.
Note that in both studies, ingroup norm perception is
descriptively less exaggerated than outgroup meta-perception
(Supplementary Results), echoing prior observations—experiment
4 and supplemental experiment A in Lees and Cikara (26), experi-
ment 4 in Ruggeri et al. (32)—and prior suggestions that the two
kinds of perception might be subject to different types of inaccur-
acy (24). The nding that ingroup norm perception is descriptively
less exaggerated than outgroup meta-perception might lead to the
tempting but erroneous conclusion that ingroup norm perception
matters less than outgroup meta-perception. The opposite is true.
Ingroup norm perception matters more, at least in terms of
predicting polarization-related outcomes. The less exaggerated
nature of ingroup norm perception might even be reinterpreted
as suggesting that individuals’ feelings toward their partisan out-
group track what they perceive their ingroup members to feel
more closely than what they perceive their outgroup members
to feel.
Our ndings represent an extension and indirect challenge to
some nuanced evidence from related work (26), which found
that a condition that corrected both ingroup norm perception
and outgroup meta-perception changed participants’ own percep-
tion of obstructionism to the same extent as a condition that cor-
rected only outgroup meta-perception. In other words, adding
correction of ingroup norm perception to correction of outgroup
meta-perception did not exert any additional effect. This study,
however, did not include any condition that corrected only
ingroup norm perception (without correcting outgroup meta-
perception), rendering direct comparisons difcult. Our pilot ex-
periment teased apart the causal effects of correcting ingroup
norm perception and correcting outgroup meta-perception. We
found that correcting ingroup norm perception improved
Republicans’ actual feeling toward their partisan outgroup.
Correcting outgroup meta-perception did not.
Why does ingroup norm perception have such powerful ef-
fects? Theoretical underpinnings of its unique explanatory power
deserve unpacking. We do so in the next section by contextualiz-
ing ingroup norm perception in robust psychological forces of in-
tergroup relations and social identity.
Theoretical underpinnings of the
psychological power of ingroup norm
perception and related ingroup processes
Theorizing by political psychologists has danced around the no-
tion of ingroup norm perception but not directly recognized its im-
portance in driving affective polarization. We rst review why
ingroup norms should exert powerful inuence on group mem-
bers’ attitudes toward the outgroup, invoking mechanisms of in-
group conformity and opinion polarization. Afterward, to fully
appreciate the power of ingroup norms, we provide a critical ap-
praisal of existing explanations of affective polarization through
the lens of normative processes.
Why ingroup norm perception should drive
affective polarization
We argue that affective polarization is driven and exacerbated by
partisans mirroring what they perceive to be their ingroup’s norm
of disliking the outgroup. A key tenet of intergroup psychology is
that individuals tend to conform to fellow ingroup members.
This is because the ingroup is highly valued and seen as part of
You and Lee | 5
the self (16). Individuals seek to afrm their ingroup identity and
assimilate. They follow what they perceive to be their ingroup’s
norms in adopting and expressing attitudes (21). Indeed, causal ef-
fects of ingroup norms on personal attitudes have been docu-
mented in numerous domains (33).
For example, expressing and suppressing prejudice toward so-
cial groups are products of conforming to perceived group norms.
The more people perceive that it is socially normative and accept-
able to hold negative feelings toward a given social group, the
more negative they themselves report feeling toward that group
(34). These processes have been found to underlie regional varia-
tions in prejudice. The more people perceive others in their region
to condone prejudice, the more people express prejudicial atti-
tudes themselves (35).
Applying these principles to the political domain, if partisans
perceive a norm of fellow co-partisans feeling negatively toward
the opposing party, they are inclined to adjust their own attitudes
to match that norm. Unfortunately, partisans’ perception of the
political ingroup’s normative attitudes toward the outgroup tends
to be negatively exaggerated, as illustrated in our analyses. Such
exaggeration can be attributed to 2 cognitive processes.
First, individuals tend to perceive their group’s average attitudes
as being more extreme than their own attitudes (36, 37). This ten-
dency emerges because group members are motivated to distance
themselves from the outgroup to maintain the value and distinct-
iveness of the ingroup. They thus exaggerate differences between
the ingroup and the outgroup, leading to a more extreme ingroup
norm perception (36). Moreover, group members often base their in-
group norm perception on the prototypical ingroup member, such
as a politician with frequent media coverage, whose attitudes might
be more extreme than the average group member (27, 37).
Second, partisans are especially negatively biased when estimat-
ing their feelings and attitudes toward their partisan outgroup.
They predict experiencing more negative affect upon encountering
the outgroup’s opinions than they actually report experiencing
when it happens (38). They also estimate that they will feel more
negative if an outgroup politician succeeds in an upcoming election
than they actually report feeling after the election (39, 40).
These processes can contribute to partisans’ negatively exag-
gerated perception of the political ingroup’s normative attitudes
toward the outgroup. Insofar as partisans match their own atti-
tudes toward the outgroup to their perceived ingroup norm,
they will end up harboring more negative attitudes than the aver-
age group member. If each group member does the same, the
average ingroup attitude itself will drift negative, intensifying af-
fective polarization (37). Making matters worse, such group dy-
namics could form a feedback loop. More affectively polarized
individuals tend to follow the ingroup’s norms more (41).
Following the norm further polarizes group members, through
the processes discussed previously, creating more polarized group
members who now follow an even more extreme perceived norm,
further exacerbating affective polarization.
These ingroup norm processes should not be foreign to political
psychology, but they have not been comprehensively integrated
into theories and research on affective polarization, despite their
demonstrated role in a variety of politically related outcomes. For ex-
ample, research on partisan cue receptivity has found that cues of
fellow political ingroup members’ issue positions constitute an im-
portant inuence on one’s own political opinions (42, 43). In labora-
tory contexts, cues of ingroup norms can ip conservatives’ and
liberals’ opposition to the same politically neutral policy, simply by
telling participants that either conservative or liberal others already
supported it (44). In naturalistic contexts, the ingroup’s inuence on
political attitudes persists even for individuals who have prior knowl-
edge about a policy (45). Crucial political behaviors, such as voting,
are also inuenced by perceived ingroup norms (46, 47).
Ingroup norm processes, well studied as they are in relation to
various political attitudes and behaviors, remain under-
appreciated in the realm of affective polarization. Research in this
area, particularly over the past several years, has focused instead
on outgroup meta-perception. Although ingroup norm perception
may appear to resemble outgroup meta-perception in structure, it
is important to realize that ingroup-focused and outgroup-focused
psychological processes often feed into different group-based
biases. For example, favoritism of partisan ingroup and derogation
of partisan outgroup are separate psychological processes that do
not necessarily co-occur (20, 48). When given the choice, partisans
prefer to help their ingroup members rather than to harm their out-
group members, illustrating their attachment to and prioritization
of the political ingroup (49, 50).
Both ingroup norm perception and outgroup meta-perception
reect perception of other individuals’ attitudes, but outgroup
meta-perception does not capture and certainly is not reducible
to ingroup norm perception. If it did and if it were, our analyses
in Section 1 would have shown that outgroup meta-perception
trumps ingroup norm perception in driving polarization-related
outcomes. But we found the opposite. Ingroup norm perception
trumps outgroup meta-perception in explaining far more vari-
ance of partisan animosity and support for partisan violence.
The unique and powerful impact of ingroup norm perception
on affective polarization, we submit, is rooted in partisans’ valued
ingroup identity and, as a corollary, their motivation to conform
and assimilate to their perception of their ingroup members’ atti-
tudes. Unfortunately, when it comes to estimating one’s political
ingroup’s negative attitudes toward the outgroup, perception
tends to exaggerate reality. Exaggerated ingroup norm perception
could beget more negative feelings, which could beget more nega-
tive ingroup norm perception, resulting in a vicious cycle.
Affective polarization research has recognized the
importance of other ingroup processes but not
ingroup norm perception
Although there is a lack of research applying ingroup norm per-
ception to affective polarization, existing explanations of affective
polarization do draw on other ingroup processes. The eld evi-
dently recognizes the importance of the political ingroup in gen-
eral but not ingroup norm perception in particular. To
appreciate its central role, we offer a critical appraisal of several
existing explanations of affective polarization through the lens
of ingroup norm processes.
One account for the rise in affective polarization is that the
boundaries between political groups have become clearer in re-
cent times, because other identities have aligned more clearly
with partisan identities. This phenomenon, called ideological
sorting, makes it easier to identify ingroup and outgroup members
(51). Researchers most commonly study sorting in the context of
Democrats being more likely to lean liberal and Republicans con-
servative (48, 52, 53), but religious and racial identities have also
become more strongly sorted along party lines (54, 55). The con-
comitant rise in ideological sorting and rise in affective polariza-
tion have prompted speculation of a relation between the two (51).
We argue that ideological sorting itself could result from in-
group norm processes. There are signs that partisans shift their
ideological opinions to align with their fellow ingroup members’.
As already noted, many voters’ ideological opinions are not driven
6 | PNAS Nexus, 2024, Vol. 3, No. 10
by cohesive worldviews (43). Rather, naïve voters often take cues
from fellow ingroup members (56). Indeed, cross-lagged panel
models have found that ideological sorting is reciprocally associ-
ated with affective polarization, suggesting that ideological cohe-
sion in political groups predicts more outgroup bias, and more
outgroup bias in turn predicts more cohesive groups (51). These
ndings are compatible with the possibility that sorting heightens
affective polarization through partisans’ attachment to their pol-
itical ingroup.
Mass media or social media lter bubbles are another catalyst
for affective polarization that can act through ingroup norm per-
ception (57–59). Watching partisan media from an ingroup-
leaning source has been found to heighten affective polarization
through 2 compounding mechanisms (59). First, the media messa-
ging and content intensify negative emotions toward the out-
group. Second, these sources use ingroup members to deliver
the message, increasing the subjective value and trustworthiness
of the news content (60).
Complementing these recognized mechanisms, we add that
partisan media can also deliver unambiguous information about
ingroup norms. The medium itself cues ingroup norms, as the ac-
tual or perceived partisan leaning of each medium reects its
group afliation. Viewers are sensitive to these cues (61). When
partisan media report on political polarization, viewers conse-
quently believe the electorate is more polarized and they them-
selves dislike the outgroup more (62). In other words, partisan
media instigate the process of shifting individual attitudes to
match perceived ingroup norms.
Partisans also avoid cross-party media sources and interac-
tions with the outgroup. A lack of interactions with outgroup
members is typically associated with more negative feelings to-
ward and negative stereotypes of the outgroup, so partisans’
avoidance contributes to affective polarization (63, 64).
Unfortunately, partisans’ interest in hearing about the outgroup’s
opinions is about as high as their interest in taking out the trash;
partisans will even give up a monetary reward to avoid outgroup
information (8). Online, they choose to avoid content that cuts
across party lines (65). It has been suggested that partisans avoid
these cross-cutting opportunities because they dislike the out-
group or political discussions in general (66).
Another reason for such avoidance, we argue, is that partisans
perceive it to be normative. Group members conform to perceived
norms of their ingroup’s attitudes and behaviors. When it comes
to intergroup contact, those who believe contact is normative in-
tend to have more contact (67); equivalently, those who believe
that contact is non-normative intend to have less contact.
Positive intergroup interactions are more common in regions
where people perceive positive intergroup contact to be common
(35). Intergroup contact and outgroup bias may exhibit a recipro-
cal relationship, such that partisans who are less polarized are
more amenable to cross-party interactions. Regardless of the pre-
cise nature of this relationship, the evidence is clear that norma-
tive inuences are strong predictors of contact intentions (68).
The prevailing explanations of affective polarization surveyed
previously already draw on various ingroup processes that
emerge from political identity as a social identity group. We argue
that these explanations can be construed through the lens of in-
group norm perception. To be clear, we are not arguing that all
these explanations have equal epistemic status or drive affective
polarization to the same extent. For example, the extent to which
selective media exposure inuences affective polarization re-
mains debated (2). We do argue that there are strong theoretical
bases underlying the contention that ingroup norm perception
is a key driver of affective polarization. By implication, if we can
manipulate ingroup norm perception, it would be a potent break-
point for intervention. We pursue this direction in the next
section.
Leveraging ingroup norm perception for
interventions against affective polarization
Building on our empirical and theoretical analyses that have high-
lighted the unique psychological power of ingroup norm percep-
tion, we propose approaches to designing and evaluating
interventions that leverage it to curb affective polarization. Our
proposed approaches are inspired by various interventions that
have successfully leveraged intergroup processes (but not ingroup
norm perception) to curb affective polarization and interventions
that have leveraged ingroup norm perception to produce effective
changes in diverse attitudinal and behavioral outcomes (but not
affective polarization). We rst review these effective interven-
tions, then describe our proposed approaches, and nally identify
critical boundary conditions, derived from theoretical principles,
that deserve prioritized attention in future intervention research.
Some effective interventions have leveraged
intergroup processes (but not ingroup norm
perception) to curb affective polarization
Many existing interventions against affective polarization already
leverage intergroup psychological phenomena. They show that
intergroup processes are often more effective than directly target-
ing stereotypes or motivations to express less prejudice. The most
successful interventions tend to model established interventions
against bias in other group domains.
For example, reminding partisans of their shared identity as
Americans reduces affective polarization by way of evoking a
common ingroup identity (69, 70). Facilitating intergroup contact
(63) or positive social interactions and intimate friendships be-
tween members of opposing political groups yields effect sizes
typical of contact in other domains (71–74). Even reading about
other ingroup members having a positive interaction (i.e. “ex-
tended intergroup contact”) reduces affective polarization (75).
Finally, outgroup meta-perception interventions, by targeting
partisans’ reactive dislike of the outgroup, reduce perceptions of
obstructionism (26, 32), dehumanization (76), animus (77), and
support for partisan violence (30) toward the opposing party.
These examples demonstrate the utility of leveraging inter-
group processes to reduce affective polarization in different
forms. Meanwhile, we nd the absence of ingroup norm percep-
tion interventions from this body of work glaring. It is also surpris-
ing because individuals’ norm perceptions are not set in stone.
They are conducive to intervention, with promising results al-
ready shown in other domains (78), as described next.
Other effective interventions have leveraged
ingroup norm perception to change diverse
attitudinal and behavioral outcomes (but not
affective polarization)
While yet to be tested on affective polarization, variants of norm
perception interventions, sometimes called social comparison in-
terventions (79), have effectively changed sticky attitudes and
consequential behaviors. A classic study showed that, over the
course of a college semester, male undergraduate students
changed their attitudes toward alcohol consumption on campus
to match their perception of their peers’ attitudes by the end of
the semester (80). Follow-up studies corrected perception of the
You and Lee | 7
norm and successfully reduced college students’ alcohol con-
sumption (81, 82). Another successful norm-based intervention
found that Californian residents used less energy, as measured
by objective household electricity meter readings, if they had re-
ceived a doorhanger message saying that their neighbors had en-
gaged in energy-conserving behaviors than if they had received
doorhanger messages describing the personal and social benets
of energy conservation (83, 84). Even vehement beliefs, such as be-
lief in vaccination conspiracies during COVID-19, were suscep-
tible to norm-based messaging interventions (85).
Closer to the realm of intergroup relations, researchers have
manipulated norm perception to change attitudes toward the out-
group (86). In one study, European American undergraduate stu-
dents were asked to report their estimates of (i) the percentage
of African Americans who possessed a series of stereotypical traits
and (ii) the percentage of fellow students who believed African
Americans to possess these traits. Afterward, if students were
told that more fellow students endorsed positive stereotypes of
African Americans than they had previously estimated, they sub-
sequently reported greater endorsement of positive stereotypes;
the same effect was found for negative stereotypes. In another
study (86), if students received information that more other stu-
dents at their own college endorsed positive stereotypes of
African Americans than they had previously estimated, they sub-
sequently reported warmer feelings (i.e. higher ratings on the feel-
ings thermometer) toward African Americans, compared with
students who received information that more students at another
college had endorsed positive stereotypes. That is, it was the norm
of the ingroup (“my college”), not the norm of an outgroup (“an-
other college”), that evoked attitude assimilation. This pattern of
results also reinforces our argument that ingroup- and
outgroup-related perceptions are different processes that can pro-
duce different outcomes.
That these ingroup norm perception interventions have suc-
cessfully shifted even persistent racial stereotypes and attitudes
is promising for its application to affective polarization. The nd-
ings summarized above constitute only a small subset of the
promising results from many norm perception interventions
that have effectively changed diverse attitudes and behaviors in
a wealth of domains (79, 87). The reason they work is that norm
perceptions are dynamic. When individuals receive more accur-
ate normative information, they update their norm perception,
and subsequently shift their own beliefs to match their new per-
ceived norm (88). Building on this process, how do we design ef-
fective norm perception interventions to curb affective
polarization?
How to design and evaluate interventions that
leverage ingroup norm perception to curb
affective polarization
Informed by our review and analysis of the existing interventions,
we suggest that the most promising approach to affective polar-
ization should be to directly tackle partisans’ perception of their
ingroup’s normative levels of outgroup bias. A general reason
for our suggestion is that drawing attention to social norms can in-
crease prosocial behavior (22). A more specic reason is that prior
work has found that partisans dislike evidence of their ingroup
displaying bias against others and that such evidence leads parti-
sans to subsequently distance themselves from the ingroup (60,
89, 90). This occurs because group members are motivated to
view their ingroup positively, as their attitudes toward their in-
groups are intricately tied to their views of themselves, so they
do not want to associate themselves closely with an ingroup
that behaves negatively (11). As a corollary, partisans should be
motivated to welcome information that their political ingroup is
not as biased as they previously believed. To the extent that
they incorporate the corrective information into their own belief
and update their norm perception, it should produce an assimila-
tive shift in their personal attitude toward the outgroup.
The scaffold of such interventions already exists. Experimentally
testing a corrective ingroup norm perception intervention for curb-
ing affective polarization could be as simple as ipping the manipu-
lation of existing outgroup meta-perception interventions. Most
existing interventions that correct outgroup meta-perception
have been methodologically similar. Participants answer the de-
pendent variable as a typical outgroup member, then receive the
average outgroup member’s actual answers, and then answer the
dependent variable for themselves. Adapting the same basic struc-
ture, as illustrated in our pilot experiment (Section 1c), interven-
tions that correct ingroup norm perception can have participants
answer the dependent variable as a typical ingroup member, then
receive the average ingroup member’s actual answers, and then an-
swer the dependent variable for themselves.
Using the same basic structure to correct both ingroup norm
perception and outgroup meta-perception comes with an import-
ant advantage. It allows for direct comparison of the causal effects
of correcting the two kinds of perception against each other, much
as we have pitted their predictive effects in Sections 1a and 1b. For
instance, a 2 (correcting vs. not correcting ingroup norm percep-
tion) × 2 (correcting vs. not correcting outgroup meta-perception)
between-participant design would allow comparison of the main
effects of correcting the two kinds of perception and detection of
their potential interactions, answering a range of empirical ques-
tions: is correcting ingroup norm perception more effective than
correcting outgroup meta-perception, paralleling the consider-
ably stronger predictive effect of ingroup norm perception than
of outgroup meta-perception? Or is correcting outgroup meta-
perception more effective than correcting ingroup norm percep-
tion, perhaps because outgroup meta-perception is more exagger-
ated in the rst place, giving it more room for correction (30)? Is
correcting either kind of perception sufcient for curbing affective
polarization such that “1 + 1 = 1 rather than 2” (26)? Or do correc-
tions of the two kinds of perception exert independent effects (“1
+ 1 = 2”)?
These experimental designs can be deployed not only in arti-
cial lab or online surveys, but also in naturalistic eld settings. For
an in vivo eld intervention on social media, researchers could
run advertisements inviting users to guess either their ingroup’s
feelings toward the outgroup (ingroup norm perception) or their
outgroup’s feelings toward the ingroup (outgroup meta-
perception), and then provide correct information. By inviting
users to make their best guesses about interesting or important
facts, researchers could gamify the experience to maximize user
interest, participation, engagement, and data quality. Users could
also be incentivized (e.g. with monetary rewards) for accuracy.
Previous studies have not incentivized outgroup meta-perception,
but doing so in future studies could help elicit more truthful or ac-
curate outgroup meta-perception and ingroup norm perception,
providing better estimation of their effects.
The caveat is that for interventions to work in the intended dir-
ection, participants would need to see evidence that their ingroup
does not actually feel as negatively toward the outgroup as they
thought. If that is factually untrue, their existing negative norm
perception is likely to prevail, especially if they are constantly ex-
posed to polarized content on social media (91). But if that is
8 | PNAS Nexus, 2024, Vol. 3, No. 10
factually true, then empirical observations of less ingroup ani-
mosity toward the outgroup should effectively change norm per-
ceptions (92), again highlighting norm perception as a promising
breakpoint for intervention.
To give users further evidence of lesser polarization or to de-
liver additional waves of intervention, other social media adver-
tisements could be employed to demonstrate successful
intergroup interactions between political groups. The motivation
for doing so is that learning about other ingroup members’ suc-
cessful intergroup interactions reduces one’s own animosity to-
ward the political outgroup (74, 75). Alternatively, once users’
norm perception estimates are corrected, a follow-up screen
could encourage users to recall their own experiences of interact-
ing with a political outgroup member that was more positive than
they expected. Such social interactions tend to be positive (93),
more so than people anticipated (94, 95), giving hope for the suc-
cessful recall of positive cross-party interactions in real life, which
would reinforce the intervention.
Finally, turning to the dependent variable, affective polariza-
tion could be evaluated using multiple operationalizations.
Feelings thermometer is an obvious possibility. Engagement
with or disengagement from the political outgroup’s content
could serve as a proxy for contact acceptance or avoidance (96).
Natural language processing techniques such as topic modeling
and sentiment analysis could assess the substance of such con-
tent for mention of the political outgroup, around what themes,
with what affective content and valence (61, 97, 98). These meth-
ods lend themselves well to online settings, especially social me-
dia, in which affective polarization is so rampant that simple,
scalable, and effective norm perception interventions are urgently
needed.
Theory-based boundary conditions that deserve
prioritized research attention
A full scientic understanding of how ingroup norm perception
interventions curb affective polarization requires identifying the
boundary conditions. In the following, we specify the most im-
portant boundary conditions that we expect based on known the-
oretical properties of ingroup processes, social identity, and
intergroup relations. Each boundary condition implies an exten-
sion or a limitation of our argument that deserves prioritized em-
pirical attention. These include strength of ingroup identication,
power dynamics of intergroup context, and generalizability to
non-American political realities.
The effectiveness of ingroup norm perception interventions
might vary as a function of the strength with which an individual
identies with their partisan ingroup. What exact patterns of
moderation should be expected, however, is not straightforward.
Some ndings lead to the prediction that ingroup norm perception
interventions should be more effective for individuals who weakly
identify with their partisan ingroup; others lead to the opposite
prediction.
On the one hand, ingroup norm perception interventions might
be more effective among weak ingroup identiers, paralleling oth-
er interventions against affective polarization that have been
found more effective among those with weaker partisan identi-
cation. For example, intergroup contact effectively reduces affect-
ive polarization for Danish participants who weakly identify with
their party but not for those who strongly identify with their party
(99), presumably because strong ingroup identiers are more mo-
tivated to view the outgroup negatively and less likely to change
their attitudes toward the outgroup.
On the other hand, ingroup norm-based interventions might be
more effective among strong ingroup identiers (23) because
strong ingroup identiers are more likely to follow perceived
norms of the political ingroup’s issue positions (56). Moreover,
the unique psychological power of political ingroup norm percep-
tion is rooted in the political ingroup being a social identity group
(i.e. the political ingroup being incorporated into one’s sense of
self). When the political ingroup is a more relevant or important
social identity, an intervention leveraging the political ingroup’s
norms should be more effective. Strong ingroup identiers should
value the ingroup’s opinions more and be more motivated to
match their attitudes to the corrective norm information and
show a larger intervention effect.
Beyond the personal variable of ingroup identication strength,
a contextual variable we consider important is the nature of
power dynamics between one’s political ingroup and outgroup.
Political groups are often construed as engaging in zero-sum com-
petitions (19, 100), which have been argued to drive negatively ex-
aggerated outgroup meta-perception (26). But there are many
naturalistic situations where intergroup cooperation is necessary,
as when one party does not have enough power to push through
crucial legislation and needs to shake hands across the aisle.
Whether ingroup norm perception interventions have larger ef-
fects in competitive or cooperative contexts is unclear. Likewise,
whether outgroup meta-perception interventions have larger ef-
fects in competitive or cooperative contexts is also unclear, be-
cause the evidence virtually always comes from competitive
political contexts (26, 76, 101), and to our knowledge, there is no
relevant study that has systematically compared effects in com-
petitive vs. cooperative contexts, though some existing data
should allow for such comparisons (32).
An even broader source of contextual variation is cross-national
differences in political systems and climates. Much of the scholar-
ship on affective polarization has focused, theoretically and empir-
ically, on American politics, but the phenomenon of affective
polarization is evident in many political systems (102–104), not
just in the United States. We recognize that the American political
context might be convenient for research on this topic both because
there are only 2 major parties (so political ingroup and outgroup are
easily identied) and because partisan hatred and toxicity currently
run high (1). These attributes, while handy, can be a cause for scien-
tic concern. The American political system that heightens the
sense of zero-sum competition between two dominant parties
might engender a unique avor of affective polarization, sustained
by powerful intergroup forces between “my allies” in a single in-
group vs. “my enemies” in a single outgroup, that is different from
what is found in other political systems or realities, such as coun-
tries with multiple major parties, countries with less political grid-
lock and sectarianism (105), more authoritarian regimes, or places
going through structural political changes.
Do the ingroup norm perception interventions that work in the
unique American political context also work elsewhere? For ex-
ample, do they work in countries where partisan identity is not
the most relevant or salient political identity? Do they work in
multiparty systems, in which the political ingroup could permeate
party boundaries (106) and in which it is less clear whether all par-
ties other than one’s own are political outgroups? Future work
should strategically identify political contexts that vary on these
parameters and test the extent to which ingroup norm perception
interventions are effective across such contexts. The goal of this
empirical strategy is to use limited resources (e.g. researchers’
time and money) wisely to generate evidence that is maximally
You and Lee | 9
informative about the generalizability of intervention effective-
ness across a vast theoretical space.
Conclusions
Throughout this Perspective piece, we have highlighted the power
of ingroup norm perception in driving affective polarization.
Evidence from 3 studies supports this central idea. Partisans’ per-
ception of their political ingroup’s normative attitudes toward
their political outgroup is a strong predictor of their own attitudes
toward the political outgroup. Ingroup norm perception has more
robust predictive effects on polarization-related outcomes and
explains considerably more variance than does outgroup meta-
perception. Correcting ingroup norm perception can improve atti-
tudes toward the political outgroup.
The unique impact of ingroup norm perception is grounded in
social and psychological forces that have been well established in
other group domains. Partisans generally perceive that the aver-
age ingroup member feels more negatively toward the political
outgroup than they themselves feel. Conforming to this negative-
ly exaggerated ingroup norm perception, partisans become more
affectively polarized.
Existing explanations of and interventions against affective po-
larization have drawn on some aspects of the political ingroup but
have not explicitly recognized the power of ingroup norm percep-
tion. Our critical appraisal of existing explanations suggests that
they could be construed through the lens of normative processes.
Our survey of existing interventions suggests that ingroup norm
perception interventions have been found effective for changing a
multitude of attitudes and behaviors, even sticky ones such as racial
attitudes and energy-conserving behaviors. These observations re-
inforce our argument that correcting norm perception is a promis-
ing approach for curbing affective polarization. The stage is set for
designing, testing, and evaluating such interventions in the eld.
If they work, there can be further downstream benets of in-
corporating ingroup norm perception into strategies for changing
broader attitudes toward political others. For example, consider-
ing that affective polarization predicts ideological polarization
and cross-partisan competition/cooperation (2, 3), changing in-
group norm perception holds the promise for directly improving
these outcomes or indirectly improving them through curbing af-
fective polarization. Such strategies would echo prior success in
tackling sacred values underlying international conicts and ne-
gotiations by making symbolic concessions that reduce toxic af-
fective intensity (107).
To conclude, much work on political attitudes, including af-
fective polarization, is built on the theoretical premise that polit-
ical groups invoke social identity. That means they should display
psychological properties common to social identity groups in oth-
er domains. One of the most robust properties is that fellow in-
group members’ attitudes are vital to the formation of one’s
own attitudes. Prevailing scientic explanations of affective polar-
ization, without properly incorporating ingroup norms, are at best
an incomplete perspective and at worst a failure to recognize the
impact of crucial mental processes. We urge scholars and practi-
tioners to stop ignoring the power of ingroup norm perception in
explaining and curbing affective polarization.
Materials and methods
Our original study and pilot experiment were approved by the re-
search ethics board at the University of Toronto (RIS Human
Protocol #42378). All participants provided informed consent.
Acknowledgments
The authors thank James Jiang and Nicole Velev for research as-
sistance and Noah Laskey for feedback.
Supplementary Material
Supplementary material is available at PNAS Nexus online.
Funding
This work was supported by the John Templeton Foundation
(Applied Research on Intellectual Humility to S.W.S.L.); the
Social Sciences and Humanities Research Council of Canada
(Insight Development Grant 430-2021-00060 and Insight Grant
435-2017-0127 to S.W.S.L.); the Ontario Ministry of Research,
Innovation and Science (Early Researcher Award—Round 13 to
S.W.S.L.); and the Province of Ontario (Ontario Graduate
Scholarship 2023 to Z.T.Y.).
Author Contributions
Both authors contributed to conceptualization, investigation,
methodology, formal analysis, and project administration.
Z.T.Y. contributed to data curation, visualization, and writing—
original draft. S.W.S.L. contributed to resources, supervision, val-
idation, and writing—review and editing.
Data Availability
Data, survey materials, and analysis code associated with our ori-
ginal data and pilot experiment are available at https://osf.io/
ahy62/. Data and code for Mernyk et al., study 1 (30, 31), were de-
posited by the original authors at https://osf.io/63jfb/.
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