Exploring the dynamics of protest with automated computational tools. A Greek case study.

Big Data volume and velocity has shifted social science research towards new tools of analysis and interpretation. The fast-growing field of computational social science tackles the need to extract comprehensive knowledge out of high volumes of heterogeneous data. This requires an interdisciplinary approach, combining experts from both social and computer science. In this chapter, we present such an interdisciplinary collaboration in the context of social movement research. Based largely on the theoretical scheme of political claims analysis, the aim of the project was to map, document, and analyze the dynamics of protest and mobilization in Greece in a longitudinal perspective. To this end, a methodology for protest event and claims extraction was implemented; generic in the sense that it can be applied in every event typology, the methodology is also innovative and suitable for interdisciplinary tasks as it incorporates the human-in-the-loop. Automated newspaper data processing was performed using Natural Language Processing tools enabled by the development of , an innovative cloud-based Big Data platform.

  • ΣΥΓΓΡΑΦΕIΣ: Stathopoulou, T, Papageorgiou, H, Papanikolaou, K, Kolovou, A.
  • YEAR: 2018
  • TYPE:
  • LANGUAGE: English
  • REFERENCE: Stathopoulou, T, Papageorgiou, H, Papanikolaou, K, Kolovou, A. (2018) Exploring the dynamics of protest with automated computational tools. A Greek case study. In C. M. Stuetzer, M. Welker, & M. Egger, (Eds.), Computational Social Science in the Age of Big Data. Concepts Methodologies, Tools, and Applications. German Society for Online Research (DGOF), Herbert von Halem Verlag.
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