Real-World Political Polarization in Twitter Discussions on Inter-Ethnic Conflicts

Studies of political polarization in social media demonstrate mixed evidence for whether discussions necessarily evolve into left and right ideological echo chambers. Recent research shows that, for political and issue-based discussions, patterns of user clusterization may differ significantly, but that cross-cultural evidence of the polarization of users on certain issues is close to non-existent. Furthermore, most of the studies developed network proxies to detect users’ grouping, rarely taking into account the content of the Tweets themselves. Our contribution to this scholarly discussion is founded upon the detection of polarization based on attitudes towards political actors expressed by users in Germany, the USA and Russia within discussions on inter-ethnic conflicts. For this exploratory study, we develop a mixed-method approach to detecting user grouping that includes: crawling for data collection; expert coding of Tweets; user clusterization based on user attitudes; construction of word frequency vocabularies; and graph visualization. Our results show that, in all the three cases, the groups detected are far from being conventionally left or right, but rather that their views combine anti-institutionalism, nationalism, and pro- and anti-minority views in varying degrees. In addition to this, more than two threads of political debate may co-exist in the same discussion. Thus, we show that the debate that sees Twitter as either a platform of ‘echo chambering’ or ‘opinion crossroads’ may be misleading. In our opinion, the role of local political context in shaping (and explaining) user clusterization should not be under-estimated

Beyond Left and Right: Real-World Political Polarization in Twitter Discussions on Inter-Ethnic Conflicts

Studies of political polarization in social media demonstrate mixed evidence for whether discussions necessarily evolve into left and right ideological echo chambers. Recent research shows that, for political and issue-based discussions, patterns of user clusterization may differ significantly, but that cross-cultural evidence of the polarization of users on certain issues is close to non-existent. Furthermore, most of the studies developed network proxies to detect users’ grouping, rarely taking into account the content of the Tweets themselves. Our contribution to this scholarly discussion is founded upon the detection of polarization based on attitudes towards political actors expressed by users in Germany, the USA and Russia within discussions on inter-ethnic conflicts. For this exploratory study, we develop a mixed-method approach to detecting user grouping that includes: crawling for data collection; expert coding of Tweets; user clusterization based on user attitudes; construction of word frequency vocabularies; and graph visualization. Our results show that, in all the three cases, the groups detected are far from being conventionally left or right, but rather that their views combine anti-institutionalism, nationalism, and pro- and anti-minority views in varying degrees. In addition to this, more than two threads of political debate may co-exist in the same discussion. Thus, we show that the debate that sees Twitter as either a platform of 'echo chambering' or 'opinion crossroads' may be misleading. In our opinion, the role of local political context in shaping (and explaining) user clusterization should not be under-estimated

Study of patterns in the hyperlink structure of large sites

ABSTRACT This paper presents experimental results on websites of four universities investigated with the aim of drawing up lists of pages and links. Variants of functions approximating the experimental data are considered. The resulting approximation estimates indicate that the approximating functions proposed are of high precision

Constructive Aggression? Multiple Roles of Aggressive Content in Political Discourse on Russian YouTube

Abstract Today, aggressive verbal behavior is generally perceived as a threat to integrity and democratic quality of public discussions, including those online. However, we argue that, in more restrictive political regimes, communicative aggression may play constructive roles in both discussion dynamics and empowerment of political groups. This might be especially true for restrictive political and legal environments like Russia, where obscene speech is prohibited by law in registered media and the political environment does not give much space for voicing discontent. Taking Russian YouTube as an example, we explore the roles of two under-researched types of communicative aggression—obscene speech and politically motivated hate speech—within the publics of video commenters. For that, we use the case of the Moscow protests of 2019 against non-admission of independent and oppositional candidates to run for the Moscow city parliament. The sample of over 77,000 comments for 13 videos of more than 100,000 views has undergone pre-processing and vocabulary-based detection of aggression. To assess the impact of hate speech upon the dynamics of the discussions, we have used Granger tests and assessment of discussion histograms; we have also assessed the selected groups of posts in an exploratory manner. Our findings demonstrate that communicative aggression helps to express immediate support and solidarity. It also contextualizes the criticism towards both the authorities and regime challengers, as well as demarcates the counter-public