The 9th International Workshop on Application of Big Data for Computational Social Science (ABCSS2024)
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 15-18, 2024. (Washington DC, USA)
In conjunction with the 2024 IEEE International Conference on Big Data (IEEE BigData 2024)
Our workshops will be held as a hybrid of in-person and online.
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 20 papers will be presented in our workshop were carefully reviewed and selected from 33 submissions.
- “An Analysis of the Relationship between Online Social Capital and Social Media Experiences”. Shigenori Ohashi, Noritaka Maeda, and Jay Kishigami
- “CoT based Few-Shot Learning of Negative Comments Filtering”. Takashi Mitadera and Takehito Utsuro
- “Comparative Evaluation of Network-Based and NLP-based Methods for Detecting Conspiracy Theory Communities on YouTube”. Koki Ota and Fujio Toriumi
- “Comparing User Activity on X and Mastodon”. Shiori Hironaka, Mitsuo Yoshida, and Kazuyuki Shudo
- “Correcting Systematic Bias in LLM-Generated Dialogues Using Big Five Personality Traits”. Lorenz Sparrenberg, Tobias Schneider, Tobias Deußer, Markus Koppenborg, and Rafet Sifa
- “Data-Driven Socio-Economic Deprivation Prediction via Dimensionality Reduction: The Power of Diffusion Maps”. June Moh Goo
- “Discovering Localized Drivers of Unrest Events using Clustering and XGBoost”. Dalton Hazelwood, Deepti Joshi, Ashok Samal, and Leen-Kiat Soh
- “Emotion Classification of Lyrics through Summarization by Large Language Models”. Sho Miyakawa and Takehito Utsuro
- “Exploring Global Gender Gaps in the Blockchain Domain: Insights from LinkedIn Advertising Data”. Reham Al Tamime, Markus Strohmaier, and Ingmar Weber
- “Exploring YouTube’s Role in Shaping Political Discourse: A Case Study of the 2024 Tokyo Gubernatorial Election”. Hibiki NAKAMURA
- “JSocialFact: a Misinformation dataset from Social Media for Benchmarking LLM Accuracy”. Tomoka Nakazato, Masaki Onishi, Hisami Suzuki, and Yuya Shibuya
- “Leading the Mastodon Herd: Analysing the Traits of Influential Leaders on a Decentralised Social Media Platform”. Luke Gassmann, Ryan McConville, and Matthew Edwards
- “Narrative Simplification in Human and AI Retelling”. Yuuri Tanaka and Yasuhiro Hashimoto
- “Polarization Prism: Facilitating Diverse Viewpoint Reflection by Mining Unseen Perspectives in Social Media Polarization”. Koki Noda, Tomoki Fukuma, Toshihide Ubukata, Yoshiharu Ichikawa, Kyosuke Kambe, Yu Masubuchi, and Fujio Toriumi
- “Public Sentiment on Security Cameras”. Muhammad Fahad Khalid, Usman Muhammed, Rune Saugmann Andersen, and Mourad Oussalah
- “Quantifying Collective Emotions: Japan’s Societal Trends Through Enhanced Sentiment Index Using POMS2 and SNS”. Koutarou Tamura, Yukie Sano, and Junichi Shiozaki
- “Revealing Patterns in Artificial Earthquake Misinformation: Detecting Stubborn Conspiracy Adherents through Social Media Analysis in Japan”. Dongwoo Lim, Fujio Toriumi, and MIkihito Tanaka
- “Sentiment and Skepticism Analysis to Understand Consumer Perception of Virtual Influencers in Social Media Advertising”. Smitha Muthya Sudheendra, Maral Abdollahi, Dongyeop Kang, Jisu Huh, and Jaideep Srivastava
- “The Bidirectional Relationship between Emotional Change and Physical Movement Activities: An Analysis Using Propensity Score Matching Methods”. Zeyu Wu, Yuuki Nishiyama, and Yuya Shibuya
- “Unveiling Real-World Company Hidden Communication Patterns: Comparing Informal Large-Scale Email Network and Formal Structure”. Leonardo Di Perna, Matteo Bianchi, Matteo Matteucci, and Marco Brambilla
IMPORTANT DATES
| October |
Workshop Papers submission |
| November 4, 2024 | Notification of Acceptance/Rejection |
| TBA | Author Registration Deadline |
| November 20, 2024 | Camera-ready Submission |
| TBA | Workshops |
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.
– 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.
Main Chairs
- Fujio Toriumi, The University of Tokyo, Informatics
- Isamu Okada, Soka University, Informatics
- Hiroki Takikawa, The University of Tokyo, Sociology
- Mitsuo Yoshida, University of Tsukuba, Informatics
Drop us an email at abcss [at] css-japan.com if you have any questions.