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Principal Investigator
Principal investigator
MiklĂłs SebĆk
MiklĂłs SebĆk is a research professor of the HUN-REN Centre for Social Sciences 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 is a research professor at the Institute for Political Science, HUN-REN Centre for Social Sciences and the research director of the Hungarian Comparative Agendas Project. He also serves the research co-director of the Artificial Intelligence National Lab at CSS, the principal investigator of the V-SHIFT Momentum research project (funded by the Hungarian Academy of Sciences), and the convenor of the COMPTEXT conference. He is an international advisory board member of the Italian Political Science Review.Â
His work has appeared in Business and Politics, Computational Communication Research, East European Politics, European Journal of Political Research, European Political Science, European Political Science Review, International Journal of Parliamentary Studies, International Political Science Review, Japanese Journal of Political Science, Intersections, Journal of Comparative Politics, Journal of the Knowledge Economy, Journal of Legislative Studies, Journal of Public Budgeting, Journal of Public Policy, Parliamentary Affairs, Plos One, Policy Studies Journal, Political Analysis, Socio-Economic Review and White House Studies.
His book chapters have been published with Oxford and Palgrave. He served as the editor for the first Hungarian handbook on âQuantitative Text Analysis and Text Mining in Political Scienceâ (LâHarmattan, 2016) and on âText Mining and Artificial Intelligence in Râ (Typotex, 2021), and most recently as co-editor of Policy Agendas in Autocracy, and Hybrid Regimes: The Case of Hungary (Palgrave, 2021).
Selected Publications
2024 (forthcoming) Staying on the Democratic Script? A Deep Learning Analysis of the Speechmaking of U.S. Presidents (Co-authors: Amnon Cavari, Ăkos MĂĄtĂ©), Policy Studies Journal.
2023 Comparative European legislative research in the age of large-scale computational text analysis: A review article (Co-authors: Sven-Oliver Proksch, Christian Rauh, PĂ©ter Visnovitz, GergĆ BalĂĄzs, Jan Schwalbach), International Political Science Review, 0(0). https://doi.org/10.1177/01925121231199904.
2023 The Transparency of Constitutional Reasoning: A Text Mining Analysis of the Hungarian Constitutional Court’s Jurisprudence (Co-authors: Fruzsina GĂĄrdos-Orosz, Rebeka Kiss, IstvĂĄn JĂĄray), Studia Iuridica Lublinensia 32 (3): 11-44. doi:10.17951/sil.2023.32.3.11-44. Repository link.
2023 Machine Translation as an Underrated Ingredient? Solving Classification Tasks with Large Language Models for Comparative Research (Co-authors: Ăkos MĂĄtĂ©, Lukasz Wordliczek, Dariusz Stolicki, ĂdĂĄm Feldmann), Computational Communication Research 5 (2): 1-34. doi:10.5117/CCR2023.2.6.MATE. Repository link.
2023 Introducing HUNCOURT: A New Open Legal Database Covering the Decisions of the Hungarian Constitutional Court for Between 1990 and 2021 (Co-authors: Rebeka Kiss, IstvĂĄn JĂĄray), Journal of Knowledge Economy, https://doi.org/10.1007/s13132-023-01395-6. Repository link.
2022 How OrbĂĄn won? Neoliberal disenchantment and the grand strategy of financial nationalism to reconstruct capitalism and regain autonomy. Socio-Economic Review, https://doi.org/10.1093/ser/mwab052.
2022 Measuring legislative stability â A new approach with data from Hungary, (Co-authors: BĂĄlint György Kubik, Csaba MolnĂĄr, IstvĂĄn JĂĄray, Anna SzĂ©kely), European Political Science 21: 491â521. doi:10.1057/s41304-022-00376-8. Repository link.
2022 Punctuated Equilibrium and Progressive Friction in Socialist Autocracy, Democracy and Hybrid Regimes (Co-authors: Ăgnes M. BalĂĄzs, Csaba MolnĂĄr), Journal of Public Policy 42 (2): 247â69. doi:10.1017/S0143814X21000143. Repository link.
2021 The (real) need for a human touch: testing a human-machine hybrid topic classification workflow on a New York Times corpus, Quality & Quantity 56, 3621-3643. doi: 10.1007/s11135-021-01287-4. Repository link.
2021 The effect of central bank communication on sovereign bond yields: The case of Hungary (Co-authors: Ăkos MĂĄtĂ© and TamĂĄs Barczikay), Plos One 16 (2). doi:10.1371/journal.pone.0245515. Repository link.
2020 The Multiclass Classification of Newspaper Articles with Machine Learning: The Hybrid Binary Snowball Approach (Co-author: ZoltĂĄn Kacsuk), Political Analysis 29 (2): 236â49. doi:10.1017/pan.2020.27. Repository link.
Books in Hungarian
For a Hungarian version, see: https://poltextlab.com/sebok-miklos.Â