The promise and pitfalls of cross-partisan conversations for reducing affective polarization: Evidence from randomized experiments

Abstract

Organizations, activists, and scholars hope that conversations between outpartisans (supporters of opposing political parties) can reduce affective polarization (dislike of outpartisans) and bolster democratic accountability (e.g., support for democratic norms). We argue that such conversations can reduce affective polarization but that these effects are likely to be conditional on topic, being especially likely if the conversations topics avoid discussion of areas of disagreement; usually not persist long-term; and be circumscribed, not affecting attitudes toward democratic accountability. We support this argument with two unique experiments where we paired outpartisan strangers to discuss randomly assigned topics over video calls. In study 1, we found that conversations between outpartisans about their perfect day dramatically decreased affective polarization, although these impacts decayed long-term. Study 2 also included conversations focusing on disagreement (e.g., why each supports their own party), which had no effects. Both studies found little change in attitudes related to democratic accountability.

Affective polarization in crosscutting communication networks: Offline and online evidence from Spain

“…In this paper, I focus on one potential source of affective polarization frequently featured in both academic and popular debate-namely the communication that flows horizontally between citizens in their informal social networks and the extent to which they comprise dissenting perspectives and opinions (Iyengar et al, 2019;Levendusky and Stecula, 2021;Santoro and Broockman, 2022). I refer to the communication that occurs between citizens with various political voting preferences as crosscutting communication, in keeping with earlier studies (e.g., Mutz, 2002Mutz, , 2006Lee et al, 2015;Matthes et al, 2019).…”

“…Most empirical evidence so far has been based on observations of information exposure from traditional media like TV, radio, and newspapers (e.g., Kim, 2015Kim, , 2019Padró-Solanet and Balcells, 2022), as well as online sources like social media, news websites, and blogs (e.g., Garrett et al, 2014;Barberá et al, 2015;Beam et al, 2018). Fewer studies have studied the discussion in real-world offline settings (e.g., Parsons, 2010;Druckman and Levendusky, 2019;Levendusky and Stecula, 2021) and the virtual world (e.g., Wojcieszak and Price, 2010;Santoro and Broockman, 2022). Some evidence is derived from self-reported perceptions of exposure or discussion (e.g., Parsons, 2010;Garrett et al, 2014;Kim, 2015Kim, , 2019, other studies track actual exposure (e.g., Barberá, 2015;Levendusky and Stecula, 2021;Padró-Solanet and Balcells, 2022), and still, other pieces of evidence are based on experimental manipulation of crosscutting exposure or discussion (e.g., Taber and Lodge, 2006;Wojcieszak and Price, 2010;Karlsen et al, 2017;Bail et al, 2018;Druckman and Levendusky, 2019;Guess and Coppock, 2020;Wojcieszak et al, 2020;Santoro and Broockman, 2022).…”

“…Fewer studies have studied the discussion in real-world offline settings (e.g., Parsons, 2010;Druckman and Levendusky, 2019;Levendusky and Stecula, 2021) and the virtual world (e.g., Wojcieszak and Price, 2010;Santoro and Broockman, 2022). Some evidence is derived from self-reported perceptions of exposure or discussion (e.g., Parsons, 2010;Garrett et al, 2014;Kim, 2015Kim, , 2019, other studies track actual exposure (e.g., Barberá, 2015;Levendusky and Stecula, 2021;Padró-Solanet and Balcells, 2022), and still, other pieces of evidence are based on experimental manipulation of crosscutting exposure or discussion (e.g., Taber and Lodge, 2006;Wojcieszak and Price, 2010;Karlsen et al, 2017;Bail et al, 2018;Druckman and Levendusky, 2019;Guess and Coppock, 2020;Wojcieszak et al, 2020;Santoro and Broockman, 2022). Previous studies further leaned on different measures of polarization, ranging from issue (e.g., Taber and Lodge, 2006;Wojcieszak and Price, 2010;Karlsen et al, 2017;Druckman and Levendusky, 2019), and ideological polarization (e.g., Barberá, 2015;Bail et al, 2018), to elite and mass affective polarization (e.g., Garrett et al, 2014;Kim, 2015Kim, , 2019Beam et al, 2018;Guess and Coppock, 2020;Wojcieszak et al, 2020;Levendusky and Stecula, 2021;Padró-Solanet and Balcells, 2022;…”

“…There is evidence of both growing (e.g., Taber and Lodge, 2006;Wojcieszak and Price, 2010;Garrett et al, 2014;Karlsen et al, 2017;Bail et al, 2018;Kim, 2019) and attenuated (e.g., Parsons, 2010;Barberá, 2015;Beam et al, 2018;Druckman and Levendusky, 2019;Guess and Coppock, 2020;Levendusky and Stecula, 2021;Padró-Solanet and Balcells, 2022) levels of polarization linked to crosscutting communication in studies with varied designs and measurements across different modalities of communication (offline/online). Some have suggested that the implications of crosscutting communication likely have scope conditions such as the presence of deliberative norms (Wojcieszak et al, 2020;Levendusky and Stecula, 2021), neutral dissemination of information (Karlsen et al, 2017), the saliency of national identity (Padró-Solanet and Balcells, 2022), and the topic of discussion (Santoro and Broockman, 2022).…”

“…Political intergroup contacts may be most powerful if members of different political groups get to know each other on a personal plane before they learn about their attitudes and group identity. If people get a chance to uncover non-political shared values and interests, they may become less prone to develop hostile feelings once disagreeable political leanings come to the surface (Mutz, 2002;Santoro and Broockman, 2022). In sum, crosscutting communication may help participants overcome the stereotyping encouraged by groupthink by furthering their understanding of the perspectives and circumstances of out-group members.…”