Development of concept and methodology for multi-level monitoring of the state of interethnic relationswith the data from social media
Project Head: Olessia Koltsova
The project aims at development of the concept and the semi-automatic methodology for monitoring ethnosocial processes and the state of interethnic relations in Russia based on social media data. It accounts for national, regional and local levels and uses methods of automatic analysis of large collections of internet texts.
Social capital and privacy online: an urban community on a social networking site
Project leader: Olessia Koltsova
Social networking sites (SNS) provide their users with a diverse functionality for communication which s enables them to grow their social capital, but simultaneously poses risks to user privacy. This is especially true given that communication networks, as a rule, develop within the same city or the closest rural area where anonymity is not always possible.
Improving the Methodology of Automatic Text Analysis
Project leader: Sergei Koltcov
Topic modeling is a promising instrument for computational social science and digital humanities as it allows to automatically reveal thematic structure of large text collections – an immensely important task in the era of big Internet data. However, topic modeling, notably LDA as its main algorithm, has a number of problems that prevent its efficient use by social scientists, including social media analysts.
The Representation of Ukrainian Crisis in News: Frame Analysis with Topic Modelling
Media framing is an important issue in media studies and political science. Media frames have been traditionally extracted via manual content and discourse analysis. Such approach has a limited ability to deal with large text collections and is prone to subjectivity both in terms of text selection and interpretation.
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