Digital Transformation and Global Society. 4th International Conference, DTGS 2019, St. Petersburg, Russia, June 19–21, 2019, Revised Selected Papers
This volume constitutes the refereed proceedings of the 4th International Conference on Digital Transformation and Global Society, DTGS 2019, held in St. Petersburg, Russia, in June 2019.
The 56 revised full papers and 9 short papers presented in the volume were carefully reviewed and selected from 194 submissions. The papers are organized in topical sections on e-polity: governance; e-polity: politics online; e-city: smart cities and urban planning; e-economy: online consumers and solutions; e-society: computational social science; e-society: humanities and education; international workshop on internet psychology; international workshop on computational linguistics.
Information from users’ profiles on social networking sites is an important data source for analysis of the users’ psychological characteristics. Texts, video and audio files, images, public pages can be easily accessible and analyzed. We consider the ways of estimating the users’ psychological characteristics on the base of his or her profile in the social network VKontakte. We compare different machine learning models for the analysis of user's texts, such as linear regression, decision trees, random forest, support vector machine with linear, radial and sigmoidal kernels. Also we discussed the possible further stages of research including the sentiment analysis for better text description, the analysis of profile photo, and, finally, ways of combining all steps for estimating psychological characteristics of social networks users.
Participants of social networks experience a temptation to build multiple profiles/identities which are homomorphous (sometimes isomorphic, often contradictive) to their real-life identities. While this experience may be viewed as a masquerade, it’s hard to deny psychological grounds of possessing multiple online identities. Every time a social networker owns two or more profiles, they are referred to as alternative identities, irrespective of which is ‘real’. Participants: 42 social networkers 15 to 25 years old, half of them females. Each was presented an Identity Dilemma, which involves issues of online identity and moral development. The dilemma was worked out as a part of the Good Play Project (Harvard Graduate School of Education), used by permission from the developers. Semi-structured interviewing procedure included putting selected questions to the participants while discussing the dilemma issues. By classification of interview narratives the following attitudes were selected, referring to alternative identities: affective, cognitive, and behavioral. Dispersion analysis and content analysis were performed to handle the data. Differences in attitudes, dependent on age, gender and identity parameters are described.
The question if the Open Government Partnership (OGP), launched in 2011, has any impact on policies and institutions in its member-states, re-mains open. Despite several case studies revealing modest achievements of OGP to improve governance, little research has been done so far to explore this puzzle in general, using statistical means. Addressing this gap, this pilot study analyzes the impact of OGP membership on the quality of governance. Using policy feedback theory and Bayesian Structural Equation Modeling (BSEM), we have discovered that OGP might have an indirect influence on the govern-ance quality via the development of civic participation, government transparen-cy and feedback mechanisms.