The 3rd International Workshop on Application of Big Data for Computational Social Science
(IEEE BigData 2018 Workshop)
https://css-japan.com/bigdatacss2018/

Contemporary social sciences are facing a serious paradigm shift because of the developments in computer and Internet technologies, though traditional social sciences are still very important. Big data, such as digital traces of online activities and mobility records, allows us to quantify human behavior and social phenomena at a fine-grained level, yet it is global in scale, thereby complementing experimental data and theoretical and computational simulation results. In some cases, we can even employ the methods of natural sciences, including physics, chemistry or biology, in order to analyze big data. From this perspective, we will organize the workshop of “applications of big data for computational social science.” The scopes of the workshop include the applications of big data, as well as the methods for collecting and using big data for computational social science. Moreover, theoretical frameworks and computational techniques for big data are also very important topics in our workshop. In this workshop, social sciences are not limited to sociology, economics, marketing, political science, but also include informatics, complexity science, econophysics, sociophysics, culturomics and the arts.

* DATE & PLACE
December 10-13, 2018, Westin Seattle (Seattle, WA, USA)
In conjunction with The 2018 IEEE International Conference on Big Data (IEEE BigData 2018)
http://cci.drexel.edu/bigdata/bigdata2018/

* 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

* IMPORTANT DATES
- October 15, 2018 (Extended)
Due date for full workshop papers submission
- November 1, 2018
Notification of paper acceptance to authors
- November 15, 2018
Camera-ready of accepted papers
- December 10-13, 2018
Main Conference and Workshops

* SUBMISSION
We accept full papers (up to 10 pages, 6 to 8 pages are recommended) and extended abstracts (2-4 pages).
- Paper Submission Page
http://bit.ly/bigdatacss2018submission

Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to below).
https://www.ieee.org/conferences/publishing/templates.html

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

* Main Chairs
Akira Ishii, Tottori University, Social Physics
Hiroki Takikawa, Tohoku University, Sociology
Fujio Toriumi, The University of Tokyo, Informatics
Mitsuo Yoshida, Toyohashi University of Technology, Informatics
Drop us an email at bigdatacss2018 [at] ss.cs.tut.ac.jp if you have any questions.

* Program Committee Members
Kimitaka Asatani, The University of Tokyo, Artificial Intelligence
Kaoru Endo, Gakushuin University
Takashi Kamihigashi, Kobe University, Economics
Yasuko Kawahata, Gunma University, Computational Social Science
Masashi Komori, Osaka Electro-communicaiton University, Social Psychology
Asako Miura, Kwansei Gakuin University, Social Psychology
Takayuki Mizuno, National Institute of Informatics, Data Science
Isamu Okada, Soka University
Takeshi Sakaki, Hottolink Co.Ltd., Natural Language Processing
Takuto Sakamoto, The University of Tokyo
Kazutoshi Sasahara, Nagoya University, Complexity Science
Aki-hiro Sato, Kyoto University, Econophysics
Satoru Shibuya, Gakushuin University, Economics
Yoshihiko Suhara, Recruit Institute of Technology, Informatics
Masanori Takano, CyberAgent, Inc. Computational Social Science
Onur Varol, Indiana University Bloomington, Infomatics
Jonathan Zhu, City University of Hong Kong, Computational Social Science