Modeling the emergence of affective polarization in the social media society

Abstract

Rising political polarization in recent decades has hampered and gridlocked policymaking, as well as weakened trust in democratic institutions. These developments have been linked to the idea that new media technology fosters extreme views and political conflict by facilitating self-segregation into “echo chambers” where opinions are isolated and reinforced. This opinion-centered picture has recently been challenged by an emerging political science literature on “affective polarization”, which suggests that current polarization is better understood as driven by partisanship emerging as a strong social identity. Through this lens, politics has become a question of competing social groups rather than differences in policy position. Contrary to the opinion-centered view, this identity-centered perspective has not been subject to dynamical formal modeling, which generally permits hypotheses about micro-level explanations for macro-level phenomena to be systematically tested and explored. We here propose a formal model that links new information technology to affective polarization via social psychological mechanisms of social identity. Our results suggest that new information technology catalyzes affective polarization by lowering search and interaction costs, which shifts the balance between centrifugal and centripetal forces of social identity. We find that the macro-dynamics of social identity is characterized by two stable regimes on the societal level: one fluid regime, in which identities are weak and social connections heterogeneous, and one solid regime in which identities are strong and groups homogeneous. We also find evidence of hysteresis, meaning that a transition into a fragmented state is not readily reversed by again increasing those costs. This suggests that, due to systemic feedback effects, if polarization passes certain tipping points, we may experience run-away political polarization that is highly difficult to reverse.

Differential Response to Corporate Political Advocacy and Corporate Social Responsibility: Implications for Political Polarization and Radicalization

“…First, using a large sample of organic social media posts, we find novel, real-world evidence for less positive and more negative semantic responses after a firm engages in CPA and the opposite after a firm engages in CSR. These findings are important because negative sentiment is a key predictor of extreme views, radicalization, and organized political threats and violence within the social media space (Törnberg et al 2021).…”

“…Second, social media sites are a key vehicle for negative emotion, which is a primary driver of affective polarization, divisiveness, and radicalization in society (Lelkes 2016; Yarchi, Baden, and Kligler-Vilenchik 2021). As a consequence, emerging research reveals negative interactions on social media sites as a powerful predictor of political conflict and radicalization (Törnberg et al 2021). This is in part because the user experience on Facebook and Twitter is akin to “throwing individuals into the midst of a political war, forcing them to pick sides, and thus transforming the social identities into the substance of intergroup conflict” (Törnberg et al 2021, p. 13).…”

A general framework to link theory and empirics in opinion formation models

“…An important challenge in the field of opinion dynamics models is to determine the settings under which the model would be able to generate stable opinion polarization. Possible solutions here, apart from negative influence, are mass media 26 , social feedback processes 25 , social influence structure 27 , arguments exchange 28 , 29 , social identity 30 , external events 31 , or mistrust 32 . Recently, the issue of opinion polarization was successfully explained by using concepts from machine learning theory 33 .…”

Editorial: The Computational Analysis of Cultural Conflicts

“…Our capacity to respond to these crises itself appears to be in a state of crisis, as the media and communication technology through which we mobilize our response are designed not to aid agreement, but to maximize user engagement by intensifying controversy and conflict (Törnberg and Uitermark, 2020 ). At a time when we most direly need to come together in constructive alignment to face these growing crises, we have created a public sphere with a bias for the conflictual, the sensational, and the hyper-partisan, shifting discourse in ways that reduce our collective ability to constructively respond ( Rogers in this Research Topic; Törnberg, 2018 ; Gaisbauer et al, 2020 ; Rogers, 2020 ; Törnberg et al, 2021 ).…”