Book chapter
От "виртуальной лаборатории" до "социального телескопа": метафоры тематических и методологических инноваций в онлайн-исследованиях
The key trends and publications in social sciences are reviewed in the article in order to reveal and present in a systematic way the changes in dominant research topics and methods of Internet research taking place since early 2000s as well as concomitant modifications in types of available data and in our understanding of the nature of Internet communications. Particular attention is paid to leading methodological innovations and to possibilities and challenges which arise as a leading function of online research shifts from an auxiliary “mirror” of conventional lab experiments, surveys and participant observations in a prevalent mode of research of global effects of micro-interactions and source of new “social phenomenology” for many research fields, including large scale experiments on the topics of social influence and cultural diffusion, political mobilization, etc.
In book
In online social networks, high level features of user behavior such as character traits can be predicted with data from user profiles and their connections. Recent publications use data from online social networks to detect people with depression propensity and diagnosis. In this study, we investigate the capabilities of previously published methods and metrics applied to the Russian online social network VKontakte. We gathered user profile data from most popular communities about suicide and depression on VK.com and performed comparative analysis between them and randomly sampled users. We have used not only standard user attributes like age, gender, or number of friends but also structural properties of their egocentric networks, with results similar to the study of suicide propensity in the Japanese social network Mixi.com. Our goal is to test the approach and models in this new setting and propose enhancements to the research design and analysis. We investigate the resulting classifiers to identify profile features that can indicate depression propensity of the users in order to provide tools for early depression detection. Finally, we discuss further work that might improve our analysis and transfer the results to practical applications.
In this paper we propose two novel methods for analyzing data collected from online social networks. In particular we will do analyses on Vkontake data (Russian online social network). Using biclustering we extract groups of users with similar interests and find communities of users which belong to similar groups. With triclustering we reveal users’ interests as tags and use them to describe Vkontakte groups. After this social tagging process we can recommend to a particular user relevant groups to join or new friends from interesting groups which have a similar taste. We present some preliminary results and explain how we are going to apply these methods on massive data repositories.
This book provides an in-depth comparative analysis of inequality and the stratification of the digital sphere.
Grounded in classical sociological theories of inequality, as well as empirical evidence, this book defines ‘the digital divide’ as the unequal access and utility of internet communications technologies and explores how it has the potential to replicate existing social inequalities, as well as create new forms of stratification. The Digital Divide examines how various demographic and socio-economic factors including income, education, age and gender, as well as infrastructure, products and services affect how the internet is used and accessed. Comprised of six parts, the first section examines theories of the digital divide, and then looks in turn at:
Highly developed nations and regions (including the USA, the EU and Japan); Emerging large powers (Brazil, China, India, Russia); Eastern European countries (Estonia, Romania, Serbia); Arab and Middle Eastern nations (Egypt, Iran, Israel); Under-studied areas (East and Central Asia, Latin America, and sub-Saharan Africa).Providing an interwoven analysis of the international inequalities in internet usage and access, this important work offers a comprehensive approach to studying the digital divide around the globe. It is an important resource for academic and students in sociology, social policy, communication studies, media studies and all those interested in the questions and issues around social inequality.
We combine bi- and triclustering to analyse data collected from the Russian online social network Vkontakte. Using biclustering we extract groups of users with similar interests and find communities of users which belong to similar groups. With triclustering we reveal users' interests as tags and use them to describe Vkontakte groups. After this social tagging process we can recommend to a particular user relevant groups to join or new friends from interesting groups which have a similar taste. We present some preliminary results and explain how we are going to apply these methods on massive data repositories.
Changes in modern Russian due to the expansion of the new technologies; Russian of the Internet (Runet). Social and cultural consequences of the CMC-revolution.
We combine bi- and triclustering to analyse data collected from the Russian online social network Vkontakte. Using biclustering we extract groups of users with similar interests and find communities of users which belong to similar groups. With triclustering we reveal users' interests as tags and use them to describe Vkontakte groups. After this social tagging process we can recommend to a particular user relevant groups to join or new friends from interesting groups which have a similar taste. We present some preliminary results and explain how we are going to apply these methods on massive data repositories.
Conducting online interview via video applications is becoming a widespread interview mode. Such programs as Skype, Google Hangouts etc may be useful for interviews with people from different countries.
The problem is whether two modes: technically mediated and face to face, can be used as equal in the same research. We suggest an analysis for all the types of technically-mediated interviews in order to suggest the criteria of similarity using comparative cases. The empirical research reveals the differences that may be detected in interviewing process and whether they influence the results.
The article reflects some potentially distorting circumstances and suggests how to avoid them.
Objective: The objective of the study was threefold. First, we examined whether extraversion contributes to the evaluations of an online social network user’s physical attractiveness made by professional recruiters. We studied if this relationship is mediated by a degree of user’s activity and popularity among other users. Second, we presumed this relationship to be specified in terms of the five-factor theory of personality. A type of characteristic adaptation named reflected extraversion was assumed to incrementally contribute to this relationship. Reflected extraversion is a meta-perception representing one’s opinion on how extraverted one is as perceived by significant others. Third, user popularity treated as an external influence in terms of the five-factor theory was presumed to reciprocally affect reflected extraversion. Method: Profiles of 188 online social network users were assessed by four professional recruiters. The latter were asked to evaluate the physical attractiveness of the former. The users completed a number of self-report measures. Various behavioural indicators extracted from the profiles were measured. Results: Extraversion enhanced recruiter-rated physical attractiveness via two paths: user activity and user popularity. The inclusion of reflected extraversion failed to improve the model substantially. However, reflected extraversion mediated the link between trait extraversion and the indicators of user popularity but not the indicators of user activity. The reciprocal path from user popularity towards reflected extraversion was negligible. Conclusions: The study shows that extraversion may allow people to efficiently manage online networking to convince recruiters that they are physically attractive, even in the absence of any offline communications.