[CITAMS] Fwd: IEEE BigData2017 Workshop for Computational Social Science

Scott Hale scott.hale at oii.ox.ac.uk
Sun Sep 10 10:39:59 EDT 2017

With apologies for cross-posting....


IEEE BigData2017 Workshop
The 2nd International Workshop on Application of Big Data for Computational
Social Science 2017
Dec. 11-14, 2017
Boston, MA, USA

SUBMISSIONS DUE: Sep. 30, 2017

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.”


- 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


- Sep. 30, 2017: Due date for workshop papers submission
- Nov.1, 2017: Notification of paper acceptance to authors
- Nov.15, 2017: Camera-ready of accepted papers
- Dec. 11-14, 2017: Workshops


We accept full papers (up to 10 pages, 6 to 8 pages are recommended) and
extended abstracts (2-4 pages). Papers should be formatted to IEEE Computer
Society Proceedings Manuscript Formatting Guidelines. See link to
formatting instructions below:
Please submit your paper here:


Akira Ishii, Tottori University
Kazutoshi Sasahara, Nagoya University
Hiroki Takikawa, Tohoku University
Fujio Toriumi, The University of Tokyo


Kimitaka Asatani, The University of Tokyo
Pete Burnap, Cardiff University
Xiaojie Chen, University of Electronic Science and Technology of China
Giovanni Luca Ciampaglia, Indiana University Network Science Institute
Kaoru Endo, Gakushuin University
Dirk Helbing, ETH Zurich
Takashi Kamihigashi, Kobe University
Yasuko Kawahata, The University of Tokyo
Masashi Komori, Osaka Electro-communication University
Asako Miura, Kwansei Gakuin University
Makoto Mizuno, Meiji University
Takayuki Mizuno, National Institute of Informatics
Isamu Okada, Soka University
Yuki Ogawa, Ritsumeikan University
Takeshi Sakaki, Hottolink Co. Ltd.
Takuto Sakamoto, The University of Tokyo
Akihiro Sato, Kyoto University
Satoru Shibuya, Gakushuin University
Naoki Sudo, Gakushuin University
Yoshihiko Suhara, Recruit Institute of Technology
Masanori Takano, Cyberagent
Onur Varol, Northeastern University Networks Science Institute
Matthew L. Williams, Cardiff University
Shinichi Yamaguchi, International University of Japan
Mitsuo Yoshida, Toyohashi University of Technology
Jonathan Zhu, City University of Hong Kong

Dr Scott Hale
Senior Data Scientist
Oxford Internet Institute, University of Oxford
Turing Fellow, Alan Turing Institute
scott.hale at oii.ox.ac.uk
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