Digital Governance Systems Laboratory ディジタルガバナンスシステム研究室

Digital Governance Systems Laboratory

In the Digital Governance Systems Lab we are interested in how ICTs can be applied to improve the delivery of public services and ultimately the quality of living. Taking context and ethical considerations into account, we study the design of such systems, build them or work with the data they generate

Key Research Topics

Voting Advice Applications

VAAs are online civic tech tools used by potential voters during an election campaign. They provide users with recommendations on candidates or political parties that are closest to their own political leanings. NLP can support VAA designers to a) formulate statements and to b) help them with stance prediction.

Online Petition Systems

Governments across the globe are re-thinking how to interact with citizens, harnessing the wisdom of the crowd. One such digital co-creation tool gaining popularity are online petition portals. ML models can be trained and optimized to classify which of the petitions are getting admitted.

Internet Voting Applications

One of the few countries besides Estonia currently experimenting with internet voting is Switzerland. So far lab members analyzed vote register data and experimented with the internet voting system baloti.

Event Participation Network Data

Governmental decision-making processes generate event-participation network data. The goal is to use ML to predict project duration and success, focusing on actor relationships and project characteristics as the key features.

Blockchain Technology and DAOs

Distributed ledgers commonly known as blockchain technology as well as distributed autonomous organizations (DAO) will also affect the way how public administrations operate. We can study different ways of decision-making and consensus mechanisms as well as their effets on public governance.

Measuring Digitalization

There are several indexes trying to capture digitalisation per country, eg by the UN, World Bank etc. It takes considerable time and expertise to gather such data. Rule based information retrieval could be a way forward to achieve more efficient measurement.

Publications View all
CnPBERT: Facilitating Chinese Online Petition Classification through Domain-Specific Pretraining
Qian Zhang, Mate Kovacs, Victor Kryssanov, Uwe Serdüt 2025 5th International Conference on Big Data Engineering and Education (BDEE)
Digital Democracy in Decentralised Autonomous Organisations
Theodor Beutel; Makode, Pam K.; Tessone, Claudio and Serdült, Uwe DAWO 2025
Temporal Dynamics and Success Patterns of Online Petitions: A Time-Series Clustering Approach
Mate Kovacs, Daniil Buryakov, Didier Gohourou, Uwe Serdult Proceedings of the 2024 10th International Conference on Robotics and Artificial Intelligence
Facilitating Online Petition Topic Categorization in South Korea: A BERT-Based Approach
Jae Hyun Son, Mate Kovacs, Shady Salama, Uwe Serdült 2025 Eleventh International Conference on eDemocracy & eGovernment (ICEDEG)

Interested in our research?

We are looking for motivated students and researchers to join our team. If you are interested in our research topics, please contact us here: serdult at fc.ritsumei.ac.jp. Potential master or PhD students are required to send along a research idea that fits with the lab’s research themes. Without such a document, we will not respond to your email.