Computational social science methods from an analytical sociology perspective: Text analysis and network modelling of Twitter data
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Abstract (EN)
In today's digital world, both the volume of accessible data for social research is increasing and the methods and modelling used to collect and analyse this data are diversifying. Rather than a question-driven or theory-driven process of data creation, collection and analysis, data-driven or method-driven social research is being designed. This thesis problematises how sociology can confront this dilemma. In this context, the study offers a content that can be a guide for social research conducted in the digital age. The study details the place and importance of mechanism-based explanation, the relationship between micro and macro levels, middle-range sociological theories and agent-based modelling for analytical sociology. In order to provide an applied example of how the analysis of digital data is carried out through computational social science methods, the study provides access to more than 2 million Turkish tweets containing the keyword "Suriyeli" from the beginning of 2011 to the end of 2022 through the Twitter Academic API. Accordingly, the study analyses tweet texts through word clouds, sentiment analysis and topic modelling on the one hand, and the interaction dynamics of Twitter users sharing these texts through network analysis and visualisation on the other. Based on the descriptive findings, it is examined how the possible network mechanisms indicated by Twitter data can be investigated through statistical network models in the context of analytical sociology. In addition, in terms of the present and future of social research, the place of traditional research methods and computational social science methods is discussed in the context of analytical sociology. In the light of the aforementioned, the ways in which analytical sociology and computational social science methods as complementary elements of each other can contribute to a social research conducted in the digital age are exemplified.
Author
Talip Akçelik
Institution
How to Cite
Talip Akçelik (Master Thesis). Computational social science methods from an analytical sociology perspective: Text analysis and network modelling of Twitter data, 2023, Hacettepe University.
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