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"Polarization (Social sciences) Case studies."
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Toward a Theory of Pernicious Polarization and How It Harms Democracies
This article compares the dynamics of polarization in the eleven case studies analyzed in this special issue to draw conclusions about antecedents of severe political and societal polarization, the characteristics and mechanisms of such polarization, and consequences of severe polarization for democracy. We find that the emergence of pernicious polarization (when a society is split into mutually distrustful “Us vs. Them” camps) is not attributable to any specific underlying social or political cleavage nor any particular institutional make-up. Instead, pernicious polarization arises when political entrepreneurs pursue their political objectives by using polarizing strategies, such as mobilizing voters with divisive, demonizing discourse and exploiting existing grievances, and opposing political elites then reciprocate with similarly polarizing tactics or fail to develop effective nonpolarizing responses. We explain how the political construction of polarization around “formative rifts” (social or political rifts that arise during the fundamental formation/reformation of a nation-state), the relative capacity of opposing political blocs to mobilize voters versus relying on mechanisms such as courts or the military to constrain the executive, and the strategic and ideological aims of the polarizing actors contribute to the emergence of its pernicious form. We analyze the consequences for democracy and conclude with reflections on how to combat pernicious polarization.
Journal Article
Deliberation across deeply divided societies : transformative moments
\"From the local level to international politics, deliberation helps to increase mutual understanding and trust, in order to arrive at political decisions of high epistemic value and legitimacy. This book gives deliberation a dynamic dimension, analysing how levels of deliberation rise and fall in group discussions, and introducing the concept of 'deliberative transformative moments' and how they can be applied to deeply divided societies, where deliberation is most needed but also most difficult to work. Discussions between ex-guerrillas and ex-paramilitaries in Colombia, Serbs and Bosnjaks in Bosnia-Herzegovina, and police officers and locals in Brazilian favelas are used as case studies, with participants addressing how peace can be attained in their countries. Allowing access to the records and transcripts of the discussions opens an opportunity for practitioners of conflict resolution to apply this research to their work in trouble spots of the world, creating a link between the theory and practice of deliberation\"-- Provided by publisher.
Book
Transformations through Polarizations and Global Threats to Democracy
This volume collects and analyzes eleven country case studies of polarized polities that are, or had been, electoral democracies, identifying the common and differing causal mechanisms that lead to different outcomes for democracy when a society experiences polarization. In this introduction, we discuss our goals for the volume, the comparative logic we apply to the cases, our overall methodological approach, and the concepts that ground the analyses. The goal of this volume is to explore pernicious polarization, i.e., when and how a society divides into mutually distrustful “us vs. them” blocs, which endangers democracy. Accordingly, we discuss the effects of such polarization on democracies, and start building a foundation for remedies. In this introductory article, we highlight and explain the inherently political and relational aspects of polarization in general and pernicious polarization in particular, present the concept of formative rifts, and discuss how opposition strategies should be part of an explanation of severe polarization.
Journal Article
Analyzing polarization of social media users and news sites during political campaigns
Social media analysis is a fast growing research area aimed at extracting useful information from social networks. Recent years have seen a great interest from academic and business world in using social media to measure public opinion. This paper presents a methodology aimed at discovering the behavior of social network users and how news sites are used during political campaigns characterized by the rivalry of different factions. As a case study, we present an analysis on the constitutional referendum that was held in Italy on December 4, 2016. A first goal of the analysis was to study how Twitter users expressed their voting intentions about the referendum in the weeks before the voting day, so as to understand how the voting trends have evolved before the vote, e.g., if there have been changes in the voting intentions. According to our study, 48% of Twitter users were polarized toward
no
, 25% toward
yes
, and 27% had a
neutral
behavior. A second goal was to understand the effects of news sites on the referendum campaign. The analysis has shown that some news sites had a strong polarization toward
yes
(unita.tv, ilsole24ore.it and linkiesta.it), some others had a
neutral
position (lastampa.it, corriere.it, huffingtonpost.it and repubblica.it) and others were oriented toward
no
(ilfattoquotidiano.it, ilgiornale.it and beppegrillo.it).
Journal Article
The Polarization Loop: How Emotions Drive Propagation of Disinformation in Online Media—The Case of Conspiracy Theories and Extreme Right Movements in Southern Europe
This paper examines the influence of emotions on political polarization, looking at online propagation of conspiracy thinking by extreme right movements in Southern Europe. Integrating insights from psychology, political science, media studies, and system theory, we propose the ‘polarization loop’, a causal mechanism explaining the cyclical relationship between extreme messages, emotional engagement, media amplification, and societal polarization. We illustrate the utility of the polarization loop observing the use of the Great Replacement Theory by extreme right movements in Italy, Portugal, and Spain. We suggest possible options to mitigate the negative effects of online polarization in democracy, including public oversight of algorithmic decission-making, involving social science and humanities in algorithmic design, and strengthening resilience of citizenship to prevent emotional overflow. We encourage interdisciplinary research where historical analysis can guide computational methods such as Natural Language Processing (NLP), using Large Language Models fine-tunned consistently with political science research. Provided the intimate nature of emotions, the focus of connected research should remain on structural patterns rather than individual behavior, making it explicit that results derived from this research cannot be applied as the base for decisions, automated or not, that may affect individuals.
Journal Article
The Internal Socio-Economic Polarization of Urban Neighborhoods: The Case of the Municipality of Nice
In continuity with the research on social segregation and the phenomenon of urban gentrification, this article examines the cohabitation patterns of populations with diametrically opposed incomes within the same neighborhood, typically observed in the city center. This phenomenon is defined here as internal socio-economic polarization. It is measured through the combination of two original indexes (poverty and wealth indexes) constructed based on income deciles per consumption unit for the year of 2017. The analysis focuses on the municipality of Nice, characterized by a low demographic dynamic, a relative concentration of seniors, and a strong tourist attractiveness, particularly in the highly polarized neighborhoods that occupy almost the entire city center. This study is complemented by a principal component analysis summarizing the characteristics of the population and housing stock in the neighborhoods of Nice. The main objective of this research is to identify and locate polarized neighborhoods within the urban context of Nice, to analyze the distinctive traits of their population and housing stock, and, finally, to highlight potential trends in the population’s socio-economic status. Moreover, the economic trajectories of polarized neighborhoods, in connection with their population and housing characteristics (such as the secondary use of a portion of the housing stock, often low-quality old buildings, social housing, and the overrepresentation of retirees), help explain the forms of socio-economic polarization observed in these neighborhoods (such as the indications of gentrification, unfinished gentrification, and sustainable cohabitation).
Journal Article
Politics on YouTube: Detecting Online Group Polarization Based on News Videos’ Comments
Technology-mediated group toxicity polarization is a major socio-technological issue of our time. For better large-scale monitoring of polarization among social media news content, we quantify the toxicity of news video comments using a Toxicity Polarization Score. For polarizing news videos, our premise is that the comments’ toxicity approximates either an “M” or “U” shaped distribution—that is, there is unevenly balanced toxicity among the comments. We evaluate our premises through a case study using a dataset of ~180,000 YouTube comments on ~3,700 real news videos from an international online news organization. Toward polarization-mitigating information systems, we build a predictive machine learning model to score the toxicity polarization of news content even when its comments are disabled or not available, as it is a current trend among news publishers to disable comments. Findings imply that the most engaging news content is also often the most polarizing, which we associate with increasing research on clickbait content and the detrimental effect of attention-based metrics on the health of online social media communities, especially news communities.
Plain Language Summary
Politics on YouTube
Findings imply that the most engaging news content is also often the most polarizing, which we associate with increasing research on clickbait content and the detrimental effect of attention-based metrics on the health of online social media communities, especially news communities.
Journal Article
The Effects of Economic Crisis on Trust
The theory of social capital rarely takes economic variables into account. This article confirms that economic factors had greater explanatory power for social trust and trust in institutions during times of economic crisis, due mainly to increased economic polarization of the population. We use Spain as a case study to analyse the impact of a number of variables on social and institutional trust before and during the economic crisis. The 2008 economic crisis in Spain resulted in a paradox: a notable decline in trust in institutions, together with a surprising increase—rather than the expected decrease—in social trust. The data analysed here also highlight the possibility that the two types of trust did not track in a mutually supportive manner due to the emergence of Movimiento 15 M, which gave rise to the appearance of new political parties such as Podemos, on the extreme left of the electoral scale.
Journal Article
Understanding Political Polarization Based on User Activity: A Case Study in Korean Political YouTube Channels
This study proposes a novel approach for measuring political polarization using a user-activity-based model. By exploiting data from comments, user activity in this study is defined based on features such as coverage, duration, and enthusiasm. To determine these features, we collect information on the activities of users from South Korean YouTube channels. Notably, the collected data of the model contains approximately 11 M comments from more than 600 K users based on 37 K videos of 77 YouTube channels. To handle the big data collection, we deploy a web-based platform called TubePlunger to collect video information (e.g., comments, replies, etc.) automatically from YouTube channels. The output of the model reveals that the users are strongly polarized because the number of neutral users is very small (approximately 8% of the total). We then applied this model to the other channels in the testing dataset to define polarization with a bias percentage and to visualize the user activity distribution. The experimental results show that there are 30 fully polarized YouTube channels (16 left-wing channels and 14 right-wing channels) with a measured bias ratio higher than 70%. Our method of analyzing social network data based on user activity provides the foundation for polarization analysis that can be applied to fields other than politics.
Journal Article