IEEE International Conference on Big Data

    Special Session on Understanding New Markets by Data Science, Social Science, and Economics

    December 15th-18th, 2024 in conjunction with IEEE BigData 2024, Wahington DC, USA

    News

    Scope

    Recent innovations with Big Data and Artificial Intelligence have created new markets and dramatically increased the importance of data. Despite these social changes, existing economics, market design, management, information systems, engineering, social science, and data science approaches to these new social issues have limitations. New market understanding schemes and solutions for social implementation are needed.

    To address these gaps, we propose a special session named “Understanding New Markets by Data Science, Social Science, and Economics” to discuss the processes and interactions among data, humans, and society with researchers from engineering, information systems, data science, social science, management, and economics. The topics to be covered in this session are practical issues for understanding new societies and markets, including analytical work with data and solutions to complex social problems. The session will cover not only cleanly formatted, homogeneous data but also heterogeneous data that influence human behavior, thinking, and intentions across different domains. Discussions will focus on how large-scale data can be used in healthcare, business management, and public systems, as well as discussions of quantitative assessments of what works in these areas and the obstacles to advancing their use. In addition to these research areas, we will explore utilizing large-scale data and designing mechanisms and institutions that consider social and cultural backgrounds across disciplines. We believe that this special session focusing on the new schemes for market understanding and design will be of great significance to academia and society.

    Topics

    We call for anyone interested in the following topics of Cross-disciplinary Data Exchange and Collaboration.

    Data-oriented Application Areas

    • Statistical Graphics and Mathematics
    • Financial, Security and Business
    • Physical Sciences and Engineering
    • Earth, Space, and Environmental Sciences
    • Text, Documents and Software
    • Social, Ambient, and Information Sciences
    • Multimedia (Image/Video/Music) Mining

    Case Studies on Data Exchange and Collaboration

    • Methods for Data Evaluation and Utilization
    • Data Management and Curation
    • Risks, Limitations, and Challenges of Data Exchange
    • Trust, Resilience, Privacy, and Security Issues
    • Design of Data

    Data-focused Cognitive Research

    • Human-Computer Interaction
    • Behavioral Science and Modeling (quantitative and qualitative approaches)
    • Theoretical Models and Experimental Methods in Human-Computer Interaction
    • Subjects and Field Experiments
    • Cognitive Science and Human Behavior

    Empirical and Comprehension Focused Data Utilization

    • Modeling of Machine Learning for Social Data
    • Ontology and Dictionary
    • Business Efficiency
    • Cognition and Perception Issues
    • Natural Language Processing, and Text Mining
    • Retrieval/recommender systems

    Market of Data

    • Process and Technologies for Data Exchange
    • Representation of Knowledge and Requirements
    • Pricing and Evaluating Mechanism of Data
    • Design of Data Platform
    • Data Acquisition, and Sensors
    • Strategic Manipulation and Incentives
    • Fairness and Social Welfare

    NLP in Social Science

    • Practical Text Mining
    • Financial/Economic Natural Language Processing
    • Summarization
    • Topic Analysis
    • Report Generation
    • Large Language Model for Social Science

    Key Dates

    NOTE: The key dates may change in the future.
    • Full paper submissions: September 8, 2024
    • Full paper submissions: September 29, 2024
    • Paper notification: October 27, 2024
    • Camera-ready deadline and copyright forms: November 17, 2024
    • Conference dates: December 15-18, 2024

    Submission

    Paper submissions should be limited to a maximum of ten (10) pages, in the IEEE 2-column format (link), including the bibliography and any possible appendices. Submissions longer than 10 pages will be rejected without review.

    Note that all accepted papers will be included in the Proceedings volume in the IEEE Xplore Digital Library. ​​Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals.

    This special session will also accept paper submissions with online participation in mind.


    Submission page has been closed. Thank you for your contribution!

    Schedules


    Go to Schedule

    Distinguished Guest

    dolores

    Ricardo Correa (PhD)

    Senior Adviser at Federal Reserve Board

    BIOGRAPHY

    Organizers

    hayashi

    Teruaki Hayashi (PhD)

    The University of Tokyo

    CV

    Teruaki Hayashi is a lecturer at The University of Tokyo. He received his Ph.D. degree in engineering from The University of Tokyo (2017). His research topics are knowledge structuring, data management, retrieval systems, and human behavior modeling, focusing on cross-disciplinary data collaboration in the data ecosystem. He is the coauthor of the book Market of Data (Kindaikagakusha, 2017), and Tools for Activating Data Marketplace (Springer, 2022). He was awarded the Dean's Award by the School of Engineering, The University of Tokyo (2017), an Excellence Award at the 23rd Annual Conference of the Japanese Society of Artificial Intelligence (2018), etc.

    sakaji

    Hiroki Sakaji (PhD)

    Hokkaido University

    CV

    Hiroki Sakaji is currently an associate professor at Hokkaido University, Japan. He got the Ph.D. degree in Engineering from the Toyohashi University of Technology (2012). His research interests are related to natural language processing, text mining concerning economics and finance. He served as an area chair of ACL and as PC members of many conferences (ACL, AAAI, IEEE BigData).

    watanabe

    Naoki Watanabe (PhD)

    Keio University

    CV

    Naoki is a professor of management science at Keio Business School. He received his Ph.D. in Economics from The State University of New York at Stony Brook (August 2003). His major academic contribution is the application of game theory to patent licensing and information markets. He has published papers on subject experiments in which voting systems and trading mechanisms as well as theoretical research. In practical activities, he has been involved in the planning of personnel algorithms for Japanese manufacturers.

    Organizing Committee

    Note: Since we are contacting to other researchers, more program committees will be added to the list.

    Co-chairs

    • Teruaki Hayashi, The University of Tokyo, Japan
    • Hiroki Sakaji, Hokkaido University, Japan
    • Naoki Watanabe, Keio University, Japan

    Program Committee

    • Chung-Chi Chen, National Institute of Advanced Industrial Science and Technology, Japan
    • Yukihisa Fujita, Toyota Motor Corporation, Japan
    • Teruaki Hayashi, The University of Tokyo, Japan
    • Mi-Young Kim, University of Alberta, Canada
    • Hirofumi Nonaka, Aichi Institute of Technology, Japan
    • Hiroki Sakaji, Hokkaido University, Japan
    • Takumi Shimizu, Keio University, Japan
    • Dominik Ślęzak, University of Warsaw & QED Software, Poland
    • Naoki Watanabe, Keio University, Japan
    • Satoshi Takahashi, The University of Electro-Communications, Japan
    • Jan Auernhammer, Stanford University, US
    • Randy Goebel, The University of Alberta, Canada
    • Hiroyasu Matsushima, Shiga University, Japan

    Contact

    Dr. Teruaki Hayashi (co-chair)

    Email: hayashi -at- sys.t.u-tokyo.ac.jp

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