The dynamics of political polarization

Levin, Simon A.; Milner, Helen V.; Perrings, Charles

doi:10.1073/pnas.2116950118

Cited by 57 publications

(35 citation statements)

References 15 publications

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“…Polarization is a central topic of academic (Bail 2021;Levin, Milner, and Perrings 2021) and public interest (Hetherington and Weiler 2018;Klein 2020). Social and legacy media are regularly preoccupied by a parade of divisive issues and events, both overtly political (e.g., abortion, school curricula) and seemingly absurd (e.g., Mr.…”

Section: Introductionmentioning

confidence: 99%

The Polarization of Popular Culture: Tracing the Size, Shape, and Depth of the Oil Spill

Rawlings¹,

Childress²

2022

Preprint

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Recent research suggests that political polarization has spilled over into otherwise mundane areas of social life. And yet, the size, shape, and depth of that spillage into popular culture is generally unknown. Relying on a sample of 135 of the most widely known movies, TV shows, musicians, sports, and leisure activities, we investigate this question. We find the oil spill into popular culture is large but loosely organized into multiple fairly shallow pools. Cultural polarization is also asymmetric. Liberals like a wide variety of popular culture, do not dislike conservative popular culture, and their tastes are more rooted in their sociodemographics. Conservatives, on the other hand, like a much narrower range of popular culture, dislike the culture created and liked by Black and urban liberals, and their tastes are more directly rooted in their political ideology. Potential implications of an asymmetric culture war, and ideas for future research, are discussed.

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Section: Introductionmentioning

confidence: 99%

The Polarization of Popular Culture: Tracing the Size, Shape, and Depth of the Oil Spill

Rawlings¹,

Childress²

2022

Preprint

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“…A more difficult task is to find evidence of the dynamic that leads to a polarized network [34]. Nevertheless, the onset of polarization in a network can be investigated through computational opinion dynamics models [35,36]. In these models [37,38] agents are represented as nodes of a graph characterized by some properties usually representing opinions or attitudes.…”

Section: Introductionmentioning

confidence: 99%

The dynamics of online polarization

Valensise¹,

Cinelli²

2022

Preprint

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Several studies pointed out that users seek the information they like the most, filter out dissenting information, and join groups of like-minded users around shared narratives. Feed algorithms may burst such a configuration toward polarization, thus influencing how information (and misinformation) spreads online. However, despite the extensive evidence and data about polarized opinion spaces and echo chambers, the interplay between human and algorithmic factors in shaping these phenomena remains unclear. In this work, we propose an opinion dynamic model mimicking human attitudes and algorithmic features. We quantitatively assess the adherence of the model's prediction to empirical data and compare the model performances with other state-of-the-art models. We finally provide a synthetic description of social media platforms regarding the model's parameters space that may be used to fine-tune feed algorithms to eventually smooth extreme polarization.

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“…The study of temporal evolution of social structure is one of the significant application domains of complex collective systems research. In particular, social fragmentation transition, i.e., transition of social states between many disconnected communities with distinct opinions and a well-connected single network with homogeneous opinions, is a timely research topic with high relevance to various current societal issues [1][2][3][4][5][6][7][8]. We had previously studied this problem using numerical simulations of adaptive social network models [9] and found that two individual behavioral traits, homophily (i.e., tendency to strengthen connections to similar individuals and weaken those to dissimilar ones) [10][11][12] and attention to novelty (i.e., tendency to strengthen connections to individuals whose opinions stand out compared to others), had the most statistically significant impact on the outcomes of social network evolution [9].…”

Section: Introductionmentioning

confidence: 99%

Social Fragmentation Transitions in Large-Scale Parameter Sweep Simulations of Adaptive Social Networks

Sayama¹

2022

Preprint

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Social fragmentation transition is a transition of social states between many disconnected communities with distinct opinions and a well-connected single network with homogeneous opinions. This is a timely research topic with high relevance to various current societal issues. We had previously studied this problem using numerical simulations of adaptive social network models and found that two individual behavioral traits, homophily and attention to novelty, had the most statistically significant impact on the outcomes of social network evolution. However, our previous study was limited in terms of the range of parameter values examined, and possible interactions between multiple behavioral traits were largely ignored. In this study, we conducted a substantially largerscale numerical simulation experiment of the same model with an expanded parameter sweep range by an order of magnitude in each parameter dimension, resulting in a total of 116,640 simulation runs. To capture nontrivial interactions among behavioral parameters, we modeled and visualized the dependence of outcome measures on the model parameters using artificial neural networks. Results show that, while the competition between homophily and attention to novelty is still the primary determinant of social fragmentation, another transition plane emerges when individuals have strong social conformity behavior, which was not previously known. This implies that social fragmentation transition can also occur in the homophily-social conformity trade-off, the two behavioral traits that have very similar microscopic individual-level effects but produce very different macroscopic collective-level outcomes, illustrating the nontrivial macroscopic dynamics of complex collective systems.

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The dynamics of political polarization

Cited by 57 publications

References 15 publications

The Polarization of Popular Culture: Tracing the Size, Shape, and Depth of the Oil Spill

The Polarization of Popular Culture: Tracing the Size, Shape, and Depth of the Oil Spill

The dynamics of online polarization

Social Fragmentation Transitions in Large-Scale Parameter Sweep Simulations of Adaptive Social Networks

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