Ivan S. Blekanov

Please Follow Us: Media roles in Twitter discussions in the United States, Germany, France, and Russia

The media are normatively expected to play significant roles in conflictual discussions within national and international communities. As previous research shows, digital platforms make scholars rethink these roles based on media behavior in online communicative environments as well as on the structural limitations of the platforms. At the same time, traditional dichotomies between information dissemination and opinion formation roles, although seemingly universal, also vary across cultures. We look at four recent conflicts of comparable nature in the United States, Germany, France, and Russia to assess the roles that legacy media have performed in the respective ad hoc discussions on Twitter. Our approach differs from previous studies, as we combine content analysis of tweets by the media and journalists with the resulting positions of the media in the discussion graphs. Our findings show that, despite the overall trend of the “elite” and regional media sticking to information dissemination, online-only media and individual journalists vary greatly in their normative strategies, and this is true across countries. We also show that combining performance in content and social network analysis may allow for reconceptualization of media roles in a more flexible way.

Multi-dimensional Echo Chambers: Language and Sentiment Structure of Twitter Discussions on the Charlie Hebdo Case

Background. Public discussions on social networks have trans-border and multilingual nature. This is especially true for conflictual discussions that reach global trending topics. Being part of the global public sphere, such discussions were expected by many observers to become horizontal, all-involving, and democratically efficient. But, with time, criticism towards the democratic quality of discussions in social media arose, with many works discovering the patterns of echo chambering in social networks. Even if so, there is still scarce knowledge on how affective hashtags work in terms of user clusterization, as well as on the differences between emotionally ‘positive’ and ‘negative’ hashtags. Objectives. We address this gap by analyzing the Twitter discussion on the Charlie Hebdo massacre of 2015. In this discussion, the Twittershpere has created #jesuischarlie and #jenesuispascharlie - two discussion clusters with, allegedly, opposite sentiments towards the journal’s ethics and freedom of speech. Research design. We were interested in whether echo chambers formed both on the hashtag level (based on language use) and within a language (based on user sentiment of French-speaking users). For data collection, we used vocabulary-based Twitter crawling. For data analysis, we employed network analytics, manual coding, web graph reconstruction, and automated sentiment analysis. Results. Our results show that #jesuischarlie and #jenesuispascharlie are alike in language distribution, with French and English being the dominant languages and the discussions remaining within the Euro-Atlantic zone. The language-based echo chambers formed in both cases. But if #jesuiuscharlie was a clear sentiment crossroads, #jenesuispascharlie was a negative echo chamber, thus allowing us to draw conclusions about multi-layer echo chambering.

Comparing Influencers: Activity vs. Connectivity Measures in Defining Key Actors in Twitter Ad Hoc Discussions on Migrants in Germany and Russia

Today, a range of research approaches is used to define the so-called influencers in discussions in social media, and one can trace both conceptual and methodological differences in how influencers are defined and tracked. We distinguish between ‘marketing’ and ‘deliberative’ conceptualization of influencers and between metrics based on absolute figures and those from social network analytics; combining them leads to better understanding of user activity and connectivity measures in defining influential users. We add to the existing research by asking whether user activity necessarily leads to better connectivity and by what metrics in online ad hoc discussions, and try to compare the structure of influencers. To do this, we use comparable outbursts of discussions on inter-ethnic conflicts related to immigration. We collect Twitter data on violent conflicts between host and re-settled groups in Russia and Germany and look at top20 user lists by eight parameters of activity and connectivity to assess the structure of influencers in terms of pro/contra-migrant cleavages and institutional belonging. Our results show that, in both discussions, the number of users involved matters most for becoming an influencer by betweenness and pagerank centralities. Also, contrary to expectations, Russian top users all in all are, in general, more neutral, while Germans are more divided, but in both countries pro-migrant media oppose anti-migrant informal leaders.

Content Sharing in Conflictual Ad - Hoc Twitter Discussions: National Patterns or Universal Trends?

Recently, the growing role of social network users in content dissemination has brought to life the concept of secondary gatekeeping – selection and republication of content already selected and published by traditional gatekeepers. Secondary gatekeeping is believed to be raising the media in-platform visibility, but it may also have negative effects such as adding to creation of echo chambers and deepening the gaps between conflicting views. Such studies are particularly relevant for emergencies or social conflicts where sharing relevant content may be crucial for lowering social unease. But till today the nature of secondary gatekeeping remains highly understudied. We have conducted a comparative study of three ad-hoc Twitter discussions on heated ethnic/racial conflicts in the USA (Ferguson riots), Germany (Koln mass abuse), and Russia (Biryulyovo anti-migrant bashings) to assess the patterns of content sharing by active discussants. We used vocabulary-based web crawling and human coding of over 1,000 tweets in randomized samples. Our results show that, in all cases, there’s weak but significant correlation between the type of user and his/her attitude to minority with the attitudes expressed in content, while it is not always true that users prefer the same gatekeeper type, e.g. online or social media. As difference between individual users remains statistically significant, this may mean that the nature of heated ad-hoc discussions facilitates formation of ‘individual-level filter bubbles’ in addition to bigger echo chambers.

Ad-hoc publics and influencers on the Russian Twitter: The case of discussion on migrants

With the emergence of discussion platforms like Twitter, the hopes rose that computermediated public sphere would become more even in access to discussion than massmediatized public sphere of the late 20 century. Scholars have argued that it will eventually form an ‘opinion crossroads’ where conflicts would be discussed by all the parties involved. But today, existing research provides mixed evidence on whether ordinary users, rather than mainstream media and institutional actors, can become influencers in discussions on current issues, e.g. relations between host and migrant communities. We focus on the Twitter discussion about an inter-ethnic conflict in Moscow’s Biryuliovo district in 2013, as well as the comparative ‘calm’ period in March 2014, and look at who were real influencers by reconstructing the discussion’s web graph, as well as analyzing and juxtaposing its metrics to figures indicating user activity. Our results show that ad hoc discussion differs dramatically from an issuebased one in terms of the influencer nature and composition; the role of active tweeting is questioned. We also show that nationalist accounts play a much bigger role than expected in both periods.

Design Muntoi web-based framework and search engine analytics for thematic virtual museums

Web is the most powerful platform to handle time, distance and space limitation in physical museum institutions. Based on recent web technology, we have been design web pages more responsive, interactive and dynamic. Web framework is designed to develop dynamic website which have a good structure, providing common library, URL mapping, session and security again attacker, database manipulation, template to generating textual output, light-weight, and often providing concept Model-View-Controller (MVC). Thematic Virtual museums system has been developing based on Go Language web programming because we are pay for attention to the performance. A language which suitable for modern computing infrastructure, light on the page, good on networking and multiprocessing. In the future development process, thematic virtual museum will be built on two sides they are from curator and visitor side. Curator will be able to provide or display a visualization of interactive contents and exhibitions with the help of analytics software that will be integrated in this framework. As our work in development of Virtual Museum in Indonesia as instrumental for supporting the achievement of the museum functions as a whole. Thematic virtual museum will be providing Data Access Layer (DAL) or Application Programming Interface (API) for integrating and accessing data sources in museum institutions. This engine working to extracting and obtain relevant information from data sources, designing to understand structure data in current database or semantically tagged of museum institutions where they used to store collections information, and system also support to manage unstructured data that have not define data-model or semantic. In this paper, we have informed our progress about development web-based framework using Go Language for thematic virtual museums, concept and design of Search Engine Analytics as a core of this system to provide closest information to the visitors align with the approach of thematic virtual museum which can be used to process data or information inside museum institutions.

Negative A/Effect: Sentiment of French-Speaking Users and Its Impact Upon Affective Hashtags on Charlie Hebdo

Studies of user sentiment on social networks like Twitter have formed a steadily growing research area. But there is still lack of knowledge on whether the discussion clusters tagged by emotionally opposite hashtags differ in sentiment distribution, both in terms of difference between hashtags and between user types, e.g. non-influencers and influential accounts. We look at two hashtags that marked the discussion on the Charlie Hebdo massacre of 2015, namely #jesuischarlie and #jenesuispascharlie. As sentiment analysis studies for the French language are rare, we elaborate our own approach to sentiment vocabulary. We apply human coding and machine learning to correct the automated sentiment assessment. Then we apply the enhanced knowledge on sentiment to both discussion segments and compare the configuration of the resulting sentiment-based nebulae in overall and francophone-only discussions. Also, we define influencers for both discussions and compare whether ordinary and institutional users differ by sentiment. We have three notable findings. First, negativity structures #jenesuispascharie more than #jesuischarlie. Second, while francophones communicate cross-sentiment inside the francophone talk, their negativity tends to cast impact upon cluster formation inside general discussions. Third, influencers in both cases tend to be more negative than positive, but institutional users bear neutral and positive sentiment more than ordinary people.

Politicians Driving Online Discussions: Are Institutionalized Influencers Top Twitter Users?

Embeddedness of politicians and political organizations in a discussion defines its level of institutionalization and creates a public arena for collaboration between publics and institutional actors. Thus, testing whether traditional hierarchies (in terms of presence of politically institutionalized actors) show up in online discussions deserves scholarly research. Moreover, it is also important to see whether more democratic societies show patterns of public involvement of politically institutionalized users that would differ from those in more authoritarian contexts.

Research of university sites internal links distribution

The article covers the university websites webpages distribution analysis in terms of the number of incoming internal links. Papers by A. Broder and R. Kumar (2000), Barabasi and Albert (1999) represent, that the distribution follows a power law with the exponent of around 2.1. However, we have recently developed a method that allows to size up websites webpages by studying just 10% of the site itself. Within the research we came across the idea, that university sites have particular characteristics, therefore they have a different exponent. This article contains the description of the experiment results conducted by the article authors, the experiment includes 97 university sites from top 500 Webometrics ranking. Power approximating curves, that describe incoming links distribution, have been drawn for each site. The average exponent among all sites is about 1.8.