Book
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10th International Conference on Social Informatics, SocInfo 2018; St.Petersburg
Modern internet technologies open a wide range of opportunities for enterprises: keeping accounts online, connecting with customers from different locations, collecting and analyzing data about their target audience and other advantages. One of the actively explored factors related to the potential success is using the Internet tools for projects presentation. The aim of this study is to identify the network distinctive patterns forming the strategies for running and maintaining an online shop’s profile on Russian social networking site vk.com. We collected data about 706 e-shops profiles on vk.com including their descriptions, information about the communities followers and posts on profile wall. For each profile we built an ego graph of followers network and calculated its centrality measures which were further used to run the k-means clustering algorithm. As a result, we identified six distinct clusters which we assume will approximate different strategies of maintaining an e-shop. These clusters differed in terms of important profile features such as community’s audience size, posting activity, followers network connectivity, the presence of “hubs”, e-shops operating mostly on vk.com or having an external head website. Considering the network-structure patterns as a result of an online shop’s formed strategy, the potential success can be estimated. Taking a monthly number of visits to a website from vk.com as a success metrics, it turns out that the centrality’s indicators themselves and generalized clusters have associations with a site-visiting frequency.
Online petitions are usually regarded as one of the most popular channels to involve citizens in the political process. In our paper we have analyzed texts and voting data (pro and against) from 9705 e-petitions submitted from 2013 until 2017 at Russian Public Initiative project. Analysis of dynamics showed stabilization of interest to this resource (emergence of a new authors, growth of “strong” petitions etc.). Studying success factors of electronic petitions at the Russian public initiative project we found out that the topic and lexical information are significant factors, as well as the level of petitions.
Online social networks (OSNs) play an increasingly important role in news dissemination and consumption, attracting such traditional media outlets as TV channels with growing online audiences. Online news streams require appropriate instruments for analysis. One of such tools is topic modeling (TM). However, TM has a set of limitations (the problem of topic number choice and the algorithm instability, among others) that must be addressed specifically for the task of sociological online news analysis. In this paper, we propose a full-cycle methodology for such study: from choosing the optimal topic number to the extraction of stable topics and analysis of TM results. We illustrate it with an analysis of online news stream of 164,426 messages formed by twelve national TV channels during a one-year period in a leading Russian OSN. We show that our method can easily reveal associations between news topics and user feedback, including sharing behavior. Additionally, we show how uneven distribution of document quantities and lengths over classes (TV channels) could affect TM results.
In this paper we analyze news text collections (clusters) via extracting their paraphrase headlines into a paraphrase graph and working with this graph. Our aim is to test whether news headline is an appropriate form of news text compression. Different types of news collections: dynamic, static and combined (both dynamic and static) clusters are analyzed and it is shown that their respective paraphrase graphs reflect the characteristics of the texts. We also automatically extract the most informationally important linked fragments of news texts, and these fragments characterize news texts as either informative, conveying some information, or publicistic ones, trying to affect the readers emotionally. It is shown that news headlines of the informative type do represent their respective compressed news reports
This book constitutes the proceedings of the Workshops held at the International Conference on Social Informatics, SocInfo 2014, which took place in Barcelona, Spain, in November 2014. This year SocInfo 2014 included nine satellite workshops: the City Labs Workshop, the Workshop on Criminal Network Analysis and Mining, CRIMENET, the Workshop on Interaction and Exchange in Social Media, DYAD, the Workshop on Exploration of Games and Gamers, EGG, the Workshop on HistoInformatics, the Workshop on Socio-Economic Dynamics, Networks and Agent-based Models, SEDNAM, the Workshop on Social Influence, SI, the Workshop on Social Scientists Working with Start-Ups and the Workshop on Social Media in Crowdsourcing and Human Computation, SoHuman.
This paper presents the results of our study of educational migration flows between Russian Federation and China. Using data from the most popular among Russian-speakers Social Networking Site VK, we explore "digital footprints" of migration, analyzing the factors influencing the size of migration flows from different Russian cities to China. We take into account different groups of parameters, in particular, geographic proximity of a city to China and to Russian educational centers, institutional presence of China, and Chinese web presence in the particular city. Resulting conditional inference tree with the relative number of educational migrants from each city as the outcome has R2 = .86
This paper provides mapping of ethnic themes and topics associated with the Caucasus on social networking site VKontakte popular in Eurasia. We collected data on virtual communities associated with major ethnic (Armenian, Georgian and Azerbaijani) and supra-ethnic ("Pan-Caucasian") groups. We combine network analysis (based on group co-membership) with LDA topic modeling (based on posts) to identify the ideologies and cultural features which unite and divide virtual Caucasus. The gap between warring nations is bridged by Pan-Caucasian virtual groups with no political ideology.
In this paper we explore main patterns of communication and cooperation in online groups created by residents of apartment buildings in St.Petersburg in social networking site “VK”. Using word-frequency analysis and Latent Dirichlet Allocation (LDA) we discovered main discussion topics in online groups. We have also found that communication of neighbors in these groups is predominantly connected with material needs and directed to solve common problems, such as related to building improvement, management company and in-fill constructions near their house. Based on online observations of city activists, we suggest that dynamic nature of SNS allows online community which is dedicated to particular problem to avoid it’s breakdown after the resolution of the original issue.
This article is talking about state management and cultural policy, their nature and content in term of the new tendency - development of postindustrial society. It mentioned here, that at the moment cultural policy is the base of regional political activity and that regions can get strong competitive advantage if they are able to implement cultural policy successfully. All these trends can produce elements of new economic development.