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IEEE BigData 2025 Workshop

The 10th International Workshop on Application of Big Data for Computational Social Science (ABCSS2025)

Despite the progress of traditional social science, modern social science is facing a serious paradigm shift due to the development of computer and Internet technologies. Human behavior and social phenomena is possible to be quantified by big data digitally tracing online activities and mobility records at a granular level. In some cases, big data can be analyzed using technologies evolving in the natural sciences, such as physics, chemistry, and biology. Experimental data and multiple results from theoretical and computational simulations complement them. Both theoretically and analytically grounded insights may open new doors of computational social sciences. From this perspective, we hold a series of annual workshops on application of big data for computational social science for several years. The scope of the workshop includes, but is not limited to, big data applications, big data collection and use, an integrated framework for theory, simulation, statistics, and experiments.

DATE & PLACE

December 8-11, 2025. (Macau SAR, China)
In conjunction with the 2025 IEEE International Conference on Big Data (IEEE BigData 2025)
Our workshop will be held on December 9 at a virtual conference (Zoom). We are considering organizing the workshop in Japan where relevant researchers can gather in person.

RESEARCH TOPICS

• Application of Sociology/Sociophysics using Big Data
• Application of Econometric/Econophysics using Big Data
• Social Media Data analyses from economic/political/social perspective
• Informatics using social Big Data
• Marketing science using social Big Data
• Business analytics using Big Data on consumer behavior
• Culturomics and art management
• Analysis of reputation of entertainment using Big Data

ACCEPTED PAPERS

The 17 papers will be presented in our workshop were carefully reviewed and selected from 24 submissions.

• A Graph k-Order Topology Learning Framework Integrating Constrained Message Passing Networks and Contrastive Learning (Xilong Li, Yan Liu, and Weihua Jiao)
• A Universal Scaling Law in Animal Movement: Quantifying Emergent System Properties from Big Data (Atushi Ishikawa, Shouji Fujimoto, and Takayuki Mizuno)
• Architecture for Deliberative Reasoning (ADR): A Computational Model of Facilitated Dialogue for Societal Questions (Takayuki Mizuno)
• Daily Emotional States Improve Predictions of Human Mobility Diversity (Kanata Takahashi, Yuuki Nishiyama, and Yuya Shibuya)
• Hybrid Models for Cyberbullying Detection Based on the Perspective of Group Polarization (Ronglei Wang, Yuefeng Ma, Fengxian Cheng, and Shijian Li)
• Impression Zombies: Characteristics Analysis and Classification of New Harmful Accounts on Social Media (Keito Uehara and Taichi Murayama)
• Investigating the impact of Japanese names and Japanese prompts on social bias in hiring decisions using LLMs (Saneyuki Okabe, Taisei Enomoto, Mamoru Komachi, and Atsushi Keyaki)
• Linking Opinion Dynamics and Emotional Expression in Online Communities: A Case Study of COVID-19 Vaccination Discourse in Japan (Qianyun Wu, Yukie Sano, Hideki Takayasu, and Misako Takayasu)
• Measuring Geographic Preferences in Social Networks Beyond Population Bias (Keitaro Takayanagi, Shiori Hironaka, and Kazuyuki Shudo)
• Mixture-of-Experts Liquid Financial Mamba Framework for Portfolio Management Based on Deep Reinforcement Learning (Fengchen Gu, Huijia Wang, Zhengyong Jiang, Ángel F. García-Fernández, Jionglong Su, and Huakang Li)
• Predicting Settlement Outcomes to Reveal Word Relations between Conflicting Claims in Financial ADR (KOUTAROU TAMURA)
• SpanishTweetsCOVID-19: A Social Media Enriched Covid-19 Twitter Spanish Dataset (Antonela Tommasel and Juan Manuel Rodriguez)
• The Circulate and Recapture Dynamic of Fan Mobility in Agency-Affiliated VTuber Networks (Tomohiro Murakami and Mitsuo Yoshida)
• The Impact of Regional Economic Conditions on Bidding Strategies in Online Labor Markets (Zhichao Wang and Zeyu Lyu)
• Understanding Toxic Interaction Across User and Video Clusters in Social Video Platforms (Qiao Wang, Liang Liu, and Mitsuo Yoshida)
• When the Crowd Agrees(or Not): Topic Effects and Reason Distributions in X’s Community Notes (Hibiki Sumioku and Yuya Shibuya)
• Whose Line Is It Anyway? Linguistic Attribution of Misinformation from Mainstream and Fringe LLMs (Han Kyul Kim, Ankur Garg, Hansea Kim, Eunjeong Joo, and Andy Skumanich)

The workshop will be held on December 9th, 2025, from 10:00 to 18:00 (Japan Standard Time). Each presentation will be allocated a 20-minute slot, consisting of a 15-minute presentation followed by a 5-minute Q&A session.

IMPORTANT DATES

SUBMISSION

We accept papers of up to 10 pages (6 to 8 pages are recommended). Submitted papers will undergo a peer review process, coordinated by the Program Committee Members of our workshop. The workshop adopts single-blind review policy.
– Paper Submission Page
Submitted papers should be formatted to the IEEE Conference Proceedings format (see link to below).
– IEEE Manuscript Templates for Conference Proceedings

All registered papers that presented in this workshop will be submitted to IEEE Xplore with main conference papers, and will be submitted into some indexing system such as Web of Science, Scopus, DBLP and others.

BigData Week in Oita 2025 (December 9-11, 2025)

BigData Week in Oita 2025 will take place at Satellite Campus Oita (near Oita Station) from December 9-11, 2025. The event aims to catalyze interdisciplinary collaboration by bringing together researchers in computational social science, experimental social science, information engineering, and economics to share recent results and discuss open challenges across these fields. See the event page for details (in Japanese).

Our workshop is primarily online. Of the three days, December 9 is reserved for authors who wish to present on site as part of BigData Week in Oita. Attendance at the event is free for all audience members. However, all workshop presenters, whether presenting online or on site, must register for IEEE BigData 2025 and pay the applicable fee.

Main Chairs

• Fujio Toriumi, The University of Tokyo, Informatics
• Isamu Okada, Soka University, Informatics
• Mitsuo Yoshida, University of Tsukuba, Informatics
• Yuya Shibuya, The University of Tokyo, Informatics
• Hiroki Takikawa, The University of Tokyo, Sociology

Drop us an email at abcss [at] css-japan.com if you have any questions.

Past Workshops

• 2024 (Hybrid Conference / Washington DC, USA)
• 2023 (Hybrid Conference / Venice, Italy)
• 2022 (Hybrid Conference / Niagara Falls, Canada)
• 2021 (Hybrid Conference / Melbourne, Australia)
• 2020 (virtual conference)
• 2019 (Thessaloniki, Greece)
• 2018 (Seattle, WA, USA)
• 2017 (Boston, MA, USA)
• 2016 (Washington D.C., USA)