The 3rd International Workshop on Application of Big Data for Computational Social Science (ABCSS2018)
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)
Our workshop will be held on December 10.
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
PROGRAM
Workshop Time Table (10:20-17:30, December 10, 2018)
ACCEPTED PAPERS
The 16 papers will be presented in our workshop were carefully reviewed and selected from 24 submissions. (The 2 papers were withdrawn.)
- Analysis of Bias in Gathering Information Between User Attributes in News Application
(Yoshifumi Seki and Mitsuo Yoshida) - Analysis of Information Polarization During Japan’s 2017 Election
(Shohei Usui, Mitsuo Yoshida, and Fujio Toriumi) - Analysis of the Influence of Internet TV Station on Wikipedia Page Views
(Hiroshi Hayano, Masanori Takano, Soichiro Morishita, Mitsuo Yoshida, and Kyoji Umemura) - Analysis of User Dwell Time on Non-News Pages
(Ryosuke Homma, Keiichi Soejima, Mitsuo Yoshida, and Kyoji Umemura) - Content-based Classification of Political Inclinations of Twitter Users
(Marco Di Giovanni, Marco Brambilla, Stefano Ceri, Florian Daniel, and Giorgia Ramponi) - Cross-Domain Hashtag Recommendation and Story Revelation in Social Media
(Mahsa Badami and Olfa Nasraoui) - Discovery of User Preferences from Big Geospatial Data Using Topic Models
(Michiharu Yamashita, Shota Katsumata, and Yusuke Fukasawa) - Evaluating Researchers through Betweenness Centrality Measures of Co-Author Networks from Academic Literature Database
(Masanori Fujita, Kenta Ishido, Hiroto Inoue, and Takao Terano) - Exploring Bias in the US Electoral College System via Big-Data Simulation
(Anthony Breitzman) - Identifying Tips Web Sites of a Specific Query based on Search Engine Suggests and the Topic Distribution
(Yohei Okawa, Shuto Kawabata, Chen Zhao, Wenbin Niu, Youchao Lin, Takehito Utsuro, and Yasuhide Kawada) - Simulation of Volatility Trading using Nikkei Stock Index Option based on Stock Bulletin Board
(Kodai Sasaki, Yui Hirose, Eiichi Umehara, Hirohiko Suwa, Yuki Ogawa, Tatsuo Yamashita, and Kota Tsubouchi) - The Influence of Social Media Writing on Online Search Behavior for Seasonal Topics: The Sociophysics Approach
(Yasuko Kawahata, Nozomi Okano, Masaru Higashi, Toshimichi Wakabayashi, and Akira Ishii) - Triadic Social Structure Facilitates Backing for Crowdfunding Projects
(Yutaka Nakai and Hiroki Takikawa) - UFO Tracker: Visualizing UFO sightings
(Vinh T. Nguyen, Vung Pham, and Tommy Dang)
IMPORTANT DATES
October 15 (Extended) |
Due date for full workshop papers submission |
November 5 |
Notification of paper acceptance to authors |
November 20 |
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
Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (see link to below).
– Manuscript Templates for Conference Proceedings
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, Megagon Labs, Informatics
- Masanori Takano, CyberAgent, Inc. Computational Social Science
- Onur Varol, Indiana University Bloomington, Infomatics
- Jonathan Zhu, City University of Hong Kong, Computational Social Science