ZORA Publication List

Publications

• Bernhard, L., Cheon, J., Lüscher, S., & Serdült, U. (2026). Junge als treibende Kraft bei den Aargauer Volksabstimmungen vom 8. März 2026 https://www.defacto.expert/2026/04/29/junge-als-treibende-kraft-bei-den-aargauer-volksabstimmungen-vom-8-maerz-2026/?print=pdf
• Bernhard, L., Cheon, J., Lüscher, S., & Serdült, U. (2026). Studie zur kantonalen Volksabstimmung vom 8. März 2026 (FOKUS Aargau). Zentrum für Demokratie Aarau (ZDA). https://www.zdaarau.ch/de/junge-als-treibende-kraft-bei-den-aargauer-volksabstimmungen-vom-8-maerz-2026/
• Lüscher, S., Serdült, U., Bernhard, L., & Cheon, J. (2026). Wer profitiert von einer Einführung von Demokratiegutscheinen? https://www.defacto.expert/2026/01/29/wer-profitiert-von-einer-einfuehrung-von-demokratiegutscheinen/
• Lüscher, S., & Serdült, U. (2026). DAO Decision-Making Simulation for Legislative Consultation: the Case of the Swiss E-ID Law 2019 2310–2319. https://scholarspace.manoa.hawaii.edu/items/595c0a89-36d4-4167-b808-2f4a47c53ec0
• Beutel, T., Makode, P. K., Tessone Claudio J., & Serdült, U. (2025). Digital Democracy in Decentralised Autonomous Organisations In M. Lustenberger, F. Spychiger, & L. Küng (Eds.), Decentralized Autonomous Organizations - Governance, Technology, and Legal Perspectives. Proceedings of the 2nd European DAO Workshop (DAWO) (pp. 35–52). Springer. https://doi.org/10.1007/978-3-032-03273-7_3
• Lüscher, S., Serdült, U., Cheon, J., & Bernhard, L. (2025). E-Collecting in der Schweiz: Akzeptanz und Reformbedarf nach dem Unterschriftenbetrug https://www.defacto.expert/2025/08/22/e-collecting-in-der-schweiz-akzeptanz-und-reformbedarf-nach-dem-unterschriftenbetrug/
• Serdült, U., Kovacs, M., Wang, O., & Wang, R. (2025). Towards Efficient and Interpretable Machine Learning for Classifying Petition Admissibility: A Case Study of the JOIN Platform (I. Lindgren, Rodríguez Bolívar Manuel Pedro, M. Janssen, E. Loukis, F. Mureddu, P. Panagiotopoulos, Viale Pereira Gabriela, & E. Tambouris, Eds.; pp. 320–335). Springer (Bücher). https://doi.org/10.1007/978-3-032-01589-1_20
• Bernhard, L., Cheon, J., Lüscher, S., Koelewijn, K. S., Sorrentino, G., & Serdült, U. (2025). FOKUS Aargau: Studie zu den Aargauer Volksabstimmungen vom 18. Mai 2025 (FOKUS Aargau, Vol. 11). Zentrum für Demokratie Aarau (ZDA). https://www.zora.uzh.ch/view/subjects/FOKUSAargau.html
• Kovacs, M., Buryakov, D., Gohourou, D., & Serdült, U. (2025). Temporal dynamics and success patterns of online petitions: a time-series clustering approach 103–109. https://doi.org/10.1145/3728985.3728996
• Siswanto, C. K., Kovacs, M., & Serdült, U. (2025). Balancing performance and computational cost for online petition processing 86–92. https://doi.org/10.1145/3728985.3729000
• Bernhard, L., Brüggemann, S., Cheon, J., & Serdült, U. (2025). FOKUS Aargau: Studie zu den Aargauer Grossratswahlen vom 20. Oktober 2024 (FOKUS Aargau). Zentrum für Demokratie Aarau (ZDA). https://report.fokus.ag/2024-10-20/aargau/
• Riyadi, A., Kovacs, M., Serdült, U., & Kryssanov, V. (2025). Benchmarking with a Language Model Initial Selection for Text Classification Tasks Machine Learning and Knowledge Extraction, 7, online. https://doi.org/10.3390/make7010003
• Son, J. H., Kovacs, M., Shady, S., & Serdült, U. (2025). Facilitating online petition topic categorization in South Korea: a BERT-based approach 198–205. https://doi.org/10.1109/ICEDEG65568.2025.11081576
• Zhang, Q., Kovacs, M., Kryssanov, V., & Serdült, U. (2025). CnPBERT: Facilitating Chinese Online Petition Classification through Domain-Specific Pretraining 80–87. https://doi.org/10.1109/BDEE67464.2025.00019
• Benli-Trichet, M., Angelico, F., De Moraes Azenha, A. L., Barlay, M., Berkachy, R., Cheon, J., Colosante, L., Fornerod, L., Gohourou, D., Hofmann, G., Huang, H., Kalberer, S., Lorusso, R., Markov, Č., Mavrov, B., Picco-Schwendener, A., Rachmantya, A. D., Seldon, N., Seo, H. S., … Serdült, U. (2025). Unraveling the digital governance systems divide (No. 4127). 1–12. https://rifdt.ifdt.bg.ac.rs/handle/123456789/4553?locale-attribute=en
• Riyadi, A., Kovacs, M., Serdült, U., & Kryssanov, V. (2024). IndoGovBERT: A Domain-Specific Language Model for Processing Indonesian Government SDG Documents Big Data and Cognitive Computing, 8, 153. https://doi.org/10.3390/bdcc8110153
• Buryakov, D., Kovacs, M., Serdült, U., & Kryssanov, V. (2024). Enhancing the design of voting advice applications with BERT language model Frontiers in Artificial Intelligence, 7, 1343214. https://doi.org/10.3389/frai.2024.1343214
• Buryakov, D., Kovacs, M., Serdült, U., & Kryssanov, V. (2024). A Multi-Label Classifier for Online Petition Systems 156–164. https://doi.org/10.1145/3657054.3657250
• Wang, R., Kovacs, M., Kryssanov, V., & Serdült, U. (2024). A BERT-based Approach to Alleviate Civic Tech Tools Overcrowding: A case study of Taiwan’s JOIN e-petition system. 695–702. https://doi.org/10.1145/3657054.3657136
• Serdült, U. (2024). Switzerland In M. Qvortrup (Ed.), Referendums Around the World (pp. 199–227). Springer. https://doi.org/10.1007/978-3-031-49096-5_9

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