Which topics spark the most heated debates on social media? Identifying those topics is not only interesting from a societ al point of view, but also allows the filtering and aggregation of social media content for disseminating news stories. In this paper, we perform a systematic methodological study of controversy detection by using the content and the network structure of social media. Unlike previous work, rather than study controversy in a single hand-picked topic and use domain specific knowledge, we take a general approach to study topics in any domain. Our approach to quantifying controversy is based on a graph-based three-stage pipeline, which involves (i) building a conversation graph about a topic; (ii) partitioning the conversation graph to identify potential sides of the controversy; and (iii) measuring the amount of controversy from characteristics of the graph. We perform an extensive comparison of controversy measures, different graph-building approaches, and data sources. We use both controversial and non-controversial topics on Twitter, as well as other external datasets. We find that our new random-walk-based measure outperforms existing ones in capturing the intuitive notion of controversy, and show that content features are vastly less helpful in this task.
Modern social media have increasingly helped people separate themselves by worldview. We watch television shows and follow blogs that agree with our views, and read Twitter streams of people we like. The result is often called the echo chamber. Scholars cite political echo chambers as partly to blame for the divisive and destructive U.S. political climate. In this paper, we introduce a mobile application called Political Blend designed to combat echo chambers: it brings people with different political beliefs together for a cup of coffee. Based on interviews, we discovered that people are open to this kind of application and feel it may help the broader political environment. The primary contribution of this work is evidence that people are open to meeting those different from them, even those who ideologically oppose them. In an environment dominated by applications matching based on similarities, we see that this is an important finding. ABSTRACT Social networks allow people to connect with each otherand have conversations on a wide variety of topics. How-ever, users tend to connect with like-minded people and readagreeable information, a behavior that leads to group polar-ization. Motivated by this scenario, we study how to takeadvantage of partial homophily to suggest agreeable contentto users authored by people with opposite views on sensitiveissues. We introduce a paradigm to present a data portraitof users, in which their characterizing topics are visualizedand their corresponding tweets are displayed using an or-ganic design. Among their tweets we inject recommendedtweets from other people considering their views on sensitiveissues in addition to topical relevance, indirectly motivatingconnections between dissimilar people. To evaluate our ap-proach, we present a case study on Twitter about a sensitivetopic in Chile, where we estimate user stances for regularpeople and nd intermediary topics. We then evaluated ourdesign in a user study. We found that recommending topi-cally relevant content from authors with opposite views in abaseline interface had a negative emotional e ect. We sawthat our organic visualization design reverts that e ect. Wealso observed signi cant individual di erences linked to eval-uation of recommendations. Our results suggest that organicvisualization may revert the negative e ects of providingpotentially sensitive content. The Internet gives individuals more choice in political news and information sources and more tools to filter out disagreeable information. Citing the preference described by selective exposure theory — people prefer information that supports their beliefs and avoid counter-attitudinal information — observers warn that people may use these tools to access only agreeable information and thus live in ideological echo chambers. We report on a field deployment of a browser extension that showed users feedback about the political lean of their weekly and all time reading behaviors. Compared to a control group, showing feedback led to a modest move toward balanced exposure, corresponding to 1-2 visits per week to ideologically opposing sites or 5-10 additional visits per week to centrist sites. This study provides the first direct assessment of the extent to which citizens encounter news and opinion challenging their political views via mass media. The widely accepted conjecture that people refuse to hear the other side is based upon self-reports of media exposure, rather than direct observation of it. In light of this long-acknowledged limitation, I leverage unique data tracking partisanship as well as actual exposure to media collected 24 7 via passive tracking devices. Contrary to previous understandings, the vast majority of citizens consume predominately centrist information, while frequently encountering ideological programming challenging their views. In fact, the best predictor of how much conservative news you watch is how much liberal news you watch, regardless of partisanship. The demonstration of widespread exposure to diverse viewpoints challenges claims asserting that resistance to political influence occurs at the exposure stage of the persuasion process. Are we the kind of creatures who are suited to govern ourselves through deliberation? We seek to answer one important component of this question: how do individuals respond to deliberation in groups with varying levels of disagreement? We use a natural experiment in which approximately 3000 individuals were divided into small groups composed of about 8-10 persons. These groups deliberated for one day about health care reform in California. We demonstrate that there is a non-monotonic effect of disagreement upon deliberative quality. Elements of deliberative quality include mutual respect, understanding, proferring of reasons and arguments, equal opportunity for discursive engagement, and neutrality. Deliberative quality is maximized at moderate levels of disagreement and lower at high levels of ideological agreement or disagreement. Furthermore, individuals exhibit higher levels of persuasion in deliberative contexts of moderate disagreement. These findings support the view that many individuals have elements of a political psychology that is well suited for deliberation. They do not recoil when encountering disagreement nor do they especially value deliberating with those who see the world in very similar ways. Instead, they regard as most successful deliberations with moderate levels of difference -- perhaps those in which they were acquire new information, perspectives, or reasons. Beyond our substantive finding, this paper offers a methodological template for experimental studies of deliberation. ABSTRACTThis article distinguishes nine senses of polarization and provides formal measures for each one to refine the methodology used to describe polarization in distributions of attitudes. Each distinct concept is explained through a definition, formal measures, examples, and references. We then apply these measures to GSS data regarding political views, opinions on abortion, and religiosity—topics described as revealing social polarization. Previous breakdowns of polarization include domain-specific assumptions and focus on a subset of the distribution’s features. This has conflated multiple, independent features of attitude distributions. The current work aims to extract the distinct senses of polarization and demonstrate that by becoming clearer on these distinctions we can better focus our efforts on substantive issues in social phenomena.