Miklós SEBŐK is a Senior Research Fellow of the Centre of Social Sciences, Hungarian Academy of Sciences (CSS HAS) in Budapest. He earned an M.A. degree in politics at the University of Virginia and an M.A. degree in economics at the Corvinus University of Budapest. He received his Ph.D. in Political Science from ELTE University of Budapest. He currently serves as the director of thet Institute for Political Science at Centre for Social Sciences and the research director of the Hungarian Comparative Agendas Project and the research co-director of the Artificial Intelligence National Lab at CSS, Budapest. His research interests include political economy and public policy and the application of text mining and machine learning methods in these fields.
Akos MATE studied political economy (PhD, Central European University) and network science (Advanced Certificate, Central European University). His main research interest is the application of quantitative text analysis and other big data methods in the political economy field. In the POLTEX project he is taking part relating to cloud infrastructure and processing large-scale text corpora.
Orsolya RING received her Ph.D. in History from ELTE University of Budapest. She is working in POLTEXT Project on creation and classification of large-scale newspaper corpora and elaboration of a domain-specific method for Hungarian sentiment analysis applying various machine learning methods. She is also working on the building of large-scale historical text corpora and its analysis by NLP methods in the Research Group Computational Social Science (CSS-RECENS).
György Márk KIS studied political science (BA, ELTE), public policy (MA, Central European University), and statistics (MSc, ELTE). During the past few years he worked at NGOs, in market research, and also served as an external contributor to the Hungarian CAP project. His primary fields are network science, the statistical modelling of complex systems and their application to the study of policy dynamics.
Csaba MOLNÁR studied political science (BA, MA Corvinus University of Budapest, BA, Nottingham Trent University). He is currently a PhD student of the Doctoral School of Political Science of the Corvinus University of Budapest. In POLTEXT, he is responsible for NLP-related and database building tasks. His main research fields are right-wing radicalism and legislative studies. He also participates in the Hungarian Comparative Agendas Project where he works on legislative database development.
Anna SZÉKELY studied sociology (BA, CUB), cultural anthropology (BA, BBTE), currently studies Regional and Environmental Economics (MA, CUB), and is a member of Széchenyi István College for Advanced Studies. Her main interests are unsupervised learning methods in text mining and the possible improvement of pre-processing methods (stemming and lemmatization) applied in quantitative text analysis for Hungarian texts. Related to POLTEXT she coordinates the OPTED project and adopts education content of POLTEXT to various platforms, such as Medium, GitHub, YouTube.
Former young scholars
- Ágnes M. Balázs
- Evelin Mészáros
- Flóra Bolonyai
- Zoltán Kacsuk