Digital Footprint of Cultural Events: The Case of Museum Night in Russia
Numerous cultural events take place around the world every year. Visitors leave digital footprint after attending such events, which is a good source of data analysis in tourist behavior and cultural studies. This research provides mapping of festival themes associated with the annual cultural event “Museum Night” on social networking site (SNS) VKontakte (VK) most popular in Russia. All posts containing the official event hashtag in Russian (#ночьмузеев) were collected from VK. To analyse the data, more than 38k posts spanning 2012 to 2019 are used. The results show the dynamic of the event web activity and changes over the last years.
Children’s interests play a key role in their psychological development. However, research in this field is associated with serious methodological problems, as it has traditionally used questionnaire surveys that cannot adequately describe the diverse and dynamic world of interests of a developing person. The article suggests using the information on VKontakte communities followed by teenagers, in order to explore their interests. Apart from being comprehensive, Vkontakte data is, unlike questionnaire answers, also uncensored. The method’s potential demonstrated through the example of a Moscow school with 674 students following 20,203 various VKontakte communities. It reveals that teenagers’ interests vary depending on their gender, age, and academic performance. The degree of such variance is demonstrated on an extended set of data on the interests of 290,182 VKontakte users. It transpires that communities followed by teenagers predict with high accuracy not only their gender (97%) and age (98%) but also the performance of the schools they attend (83%). The findings point to the heterogeneity of age-related behavior patterns, in particular to their correlation with gender and academic achievements. Acknowledgement of the heterogeneity of interests and the diversity of age-related behavior patterns creates conditions for the further development of student-centered education, in the absence of which education is becoming more and more alienated from real life, ignoring the interests of real people.
The research is devoted to data collection and processing on social networks about the current problems of the region and about interaction with administrative structures. Developed technique allowing to categorization unstructured information and to combine it with data of standard sociological poll.
ENTER2019 features cutting-edge research and industry case studies on the application of Information and Communication Technologies (ICT) in travel and tourism. Organized by the International Federation for IT and Travel & Tourism (IFITT), ENTER2019 takes place in Nicosia, Cyprus, from January 30 to February 1, 2019. This Special Issue includes 24 short research papers presented at the conference.
Russia today is a fundamentally fragmented society, with four big milieus showing divergent patterns of media use and involvement into public deliberation within a hybrid media system. Our research upon media use patterns of participants of the 'For fair elections' protest rallies of 2011-2012 shows that there is a link between media use patterns in post-industrial urban 'public counter-sphere' and the protest spill-over, for which newlyformed media clusters have played a crucial role. As Russia is the 'world's top networking community' (as stated by Comscore in 2012), the research is expanded by search for echo chambers/opinion crossroads in Russian Facebook vs. its analogue Vkontakte.
The article investigates new trends in user-generated content creation. The use of convergent mass media has become more significant lately. With the development of the Internet and emergence of new high-technology devices and means of communication it is vitally important to go beyond the boundaries of traditional communication channels. The article includes an overview of a variety of new channels.
Nowadays online social networks (Facebook, VKontake, etc.) are the part of modern life, but they are also the cause of achievement (especially academic) decline. Self-regulation and procrastination are the characteristics that can be defined as personality factors in online social network use. Procrastination is conceptualized as postponing some actions crucial to the timely completion of assignments or as a "voluntarily delay". It is defined as a self-regulatory failure, representative of low conscientiousness, high impulsivity, and thought control problems. There is some evidence of the negative role of procrastination as well as low self-regulation in academic achievements. At the same time relations between procrastination and self-regulation are still unclear. This study analyses personality factors: procrastination and self-regulation as predictors of online social network (OSN) usage intensity and intrusion. The sample consists of 321 users of OSN VKontakte, from 17 to 60 ages. OSN usage assessed by OSN Intensity scale and OSN Intrusion scale. The features of procrastination and self-regulation were also measured. Based on correlation and regression analyses was found that sex and procrastination are significant predictors of OSN intensity and intrusion. Sex differences in OSN usage were clarified. This study shows that women are more tend to use OSN and reveal negative aspects (relation, emotional, work problems) of intensity and intrusion of online social network usage.
This essay examnes the changing role of the amateur critic, the film fan who expends great effort to offer routine critiques of viewed films. It analyses 455 user generated texts from sites Afisha.ru and Kinopoisk.ru about the Russian movie Vysotskii. Thank God I’m Alive (2011). Six types of ordinary cinema reviews are described and discussed. Using a quantitative technique to analyse ordinary critical reviews, it unpacks the ways in which the roles of the amaeteur critic and professional critic are moving towards each other. The used technique is based on the allocation of topics presented in the corpus of texts, with the subsequent manual coding of these topics, and on cluster analysis (K-means method).