433 research outputs found

    Network polarization, filter bubbles, and echo chambers: An annotated review of measures and reduction methods

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    Polarization arises when the underlying network connecting the members of a community or society becomes characterized by highly connected groups with weak inter-group connectivity. The increasing polarization, the strengthening of echo chambers, and the isolation caused by information filters in social networks are increasingly attracting the attention of researchers from different areas of knowledge such as computer science, economics, social and political sciences. This work presents an annotated review of network polarization measures and models used to handle the polarization. Several approaches for measuring polarization in graphs and networks were identified, including those based on homophily, modularity, random walks, and balance theory. The strategies used for reducing polarization include methods that propose edge or node editions (including insertions or deletions, as well as edge weight modifications), changes in social network design, or changes in the recommendation systems embedded in these networks.Comment: Corrected a typo in Section 3.2; the rest remains unchange

    Minimizing Polarization and Disagreement in Social Networks

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    The rise of social media and online social networks has been a disruptive force in society. Opinions are increasingly shaped by interactions on online social media, and social phenomena including disagreement and polarization are now tightly woven into everyday life. In this work we initiate the study of the following question: given nn agents, each with its own initial opinion that reflects its core value on a topic, and an opinion dynamics model, what is the structure of a social network that minimizes {\em polarization} and {\em disagreement} simultaneously? This question is central to recommender systems: should a recommender system prefer a link suggestion between two online users with similar mindsets in order to keep disagreement low, or between two users with different opinions in order to expose each to the other's viewpoint of the world, and decrease overall levels of polarization? Our contributions include a mathematical formalization of this question as an optimization problem and an exact, time-efficient algorithm. We also prove that there always exists a network with O(n/Ļµ2)O(n/\epsilon^2) edges that is a (1+Ļµ)(1+\epsilon) approximation to the optimum. For a fixed graph, we additionally show how to optimize our objective function over the agents' innate opinions in polynomial time. We perform an empirical study of our proposed methods on synthetic and real-world data that verify their value as mining tools to better understand the trade-off between of disagreement and polarization. We find that there is a lot of space to reduce both polarization and disagreement in real-world networks; for instance, on a Reddit network where users exchange comments on politics, our methods achieve a āˆ¼60ā€‰000\sim 60\,000-fold reduction in polarization and disagreement.Comment: 19 pages (accepted, WWW 2018

    'Enclaves of exposure' : a conceptual viewpoint to explore cross-ideology exposure on social network sites

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    Previous studies indicate mixed results as to whether social media constitutes ideological echo chambers. This inconsistency may arise due to a lack of theoretical frames that acknowledge the fact that contextual and technological factors allow varying levels of cross-cutting exposure on social media. This study suggests an alternative theoretical lens, divergence of exposure ā€“ co-existence of user groups with varying degrees of cross-ideology exposure related to the same issue ā€“ as a notion that serves as an overarching perspective. We suggest that mediated spaces, such as social media groups, can serve as enclaves of exposure that offer affordances for formation of user groups irrespective of offline social distinctions. Yet social elements cause some of them to display more cross-ideology exchange than others. To establish this claim empirically, we examine two Facebook page user networks (ā€˜Sri Lankaā€™s Killing Fieldsā€™ and ā€˜Sri Lankans Hate Channel 4ā€™) that emerged in response to Sri Lankaā€™s Killing Fields, a controversial documentary broadcast by Channel 4 that accused Sri Lankan armed forces of human rights violation during the final stage of the separatist conflict in Sri Lanka. The results showed that the Facebook group network that supported the claims made by Channel 4 is more diverse in terms of ethnic composition, and is neither assortative nor disassortative across ethnicity, suggesting the presence of cross-ethnicity interaction. The pro-allegiant group was largely homogenous and less active, resembling a passive echo chamber. ā€˜Social mediationā€™ repurposes enclaves of exposure to represent polarized ideologies where some venues display cross-ideology exposure, while others resemble an ā€˜echo chamberā€™

    Modelling opinion misperception and the emergence of silence in online social system

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    In the last decades an increasing deal of research has investigated the phenomenon of opinion misperception in human communities and, more recently, in social media. Opinion misperception is the wrong evaluation by community's members of the real distribution of opinions or beliefs about a given topic. In this work we explore the mechanisms giving rise to opinion misperception in social media groups, which are larger than physical ones and have peculiar topological features. By means of numerical simulations, we suggest that the structure of connections of such communities plays indeed a role in distorting the perception of the agents about others' beliefs, but it is essentially an indirect effect. Moreover, we show that the main ingredient that generates the misperception is a spiral of silence induced by few, well connected and charismatic agents, which rapidly drives the majority of individuals to stay silent without disclosing their true belief, leading minoritarian opinions to appear more widespread throughout the community.Comment: 13 pages, 5 figures, 1 table. To be submitted soo

    Network analysis reveals open forums and echo chambers in social media discussions of climate change

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    Open Access articleAction to tackle the complex and divisive issue of climate change will be strongly influenced by public perception. Online social media and associated social networks are an increasingly important forum for public debate and are known to influence individual attitudes and behaviours yet online discussions and social networks related to climate change are not well understood. Here we construct several forms of social network for users communicating about climate change on the popular microblogging platform Twitter. We classify user attitudes to climate change based on message content and nd that social networks are characterised by strong attitude-based homophily and segregation into polarised "sceptic" and "activist" groups. Most users interact only with like-minded others, in communities dominated by a single view. However, we also nd mixed-attitude communities in which sceptics and activists frequently interact. Messages between like-minded users typically carry positive sentiment, while messages between sceptics and activists carry negative sentiment. We identify a number of general patterns in user behaviours relating to engagement with alternative views. Users who express negative sentiment are themselves the target of negativity. Users in mixed- attitude communities are less likely to hold a strongly polarised view, but more likely to express negative sentiment towards other users with di ering views. Overall, social media discussions of climate change often occur within polarising "echo chambers", but also within "open forums", mixed-attitude communities that reduce polarisation and stimulate debate. Our results have implications for public engagement with this important global challenge.Engineering and Physical Sciences Research Council (EPSRC) - Bridging the Gaps initiativ

    Of echo chambers and contrarian clubs: Exposure to political disagreement among German and Italian users of Twitter

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    Scholars have debated whether social media platforms, by allowing users to select the information to which they are exposed, may lead people to isolate themselves from viewpoints with which they disagree, thereby serving as political ā€œecho chambers.ā€ We investigate hypotheses concerning the circumstances under which Twitter users who communicate about elections would engage with (a) supportive, (b) oppositional, and (c) mixed political networks. Based on online surveys of representative samples of Italian and German individuals who posted at least one Twitter message about elections in 2013, we find substantial differences in the extent to which social media facilitates exposure to similar versus dissimilar political views. Our results suggest that exposure to supportive, oppositional, or mixed political networks on social media can be explained by broader patterns of political conversation (i.e., structure of offline networks) and specific habits in the political use of social media (i.e., the intensity of political discussion). These findings suggest that disagreement persists on social media even when ideological homophily is the modal outcome, and that scholars should pay more attention to specific situational and dispositional factors when evaluating the implications of social media for political communication

    TOWARDS AN UNDERSTANDING OF CONSPIRACY ECHO CHAMBERS ON FACEBOOK

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    Selective online exposure to information that serves to only affirm peopleā€™s opinions or is strongly aligned with their interests is considered to be a major issue in modern societies. Echo chambers, for example, are online environments in which users are only exposed to confirming opinions and alternative voices are excluded or discredited. Echo chambers are considered to be particularly dangerous, because they may lead to polarization and even radicalization. Social media facilitate the formation of echo chambers as described in the Social Identity Theory by means of homophily and depersonalization. This can be especially harmful in the case of conspiracy beliefs, where particularly extreme opinions lead to a stronger seclusion from society, encourage socially destructive actions, and curate Fake News. In our research we will assess different echo chambers in terms of actively established common patterns of consumed online information sources. To that end, we analyse the news source Likes from over 7,000 users with their approximately 1,450,000 Likes on Facebook. We intend to identify different types of Facebook echo chambers with a focus on conspiracy groups, understand distinguishing characteristics in communicative behaviour of the conspiracy groups on Facebook and explore unique characteristics of users in conspiracy echo chambers
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