Sino-German Symposium on Social Computing in Göttingen
With the rapid development of information and communication technologies, individual users, enterprises, governments and other institutions have now access to a variety of data. Such data might be used for information sharing, entertainment, understanding individual behaviors and social problems, or even making business decisions. “Social computing”, a new discipline which aims to address issues that are mostly related to social networks and big data, has attracted a lot of interest from both academia and the industry. The first Sino-German Symposium on Social Computing was successfully held in Göttingen, Germany, from August 28 to September 2, 2016. The symposium was sponsored by the Sino-German Center for Research Promotion, which brought together more than 50 researchers and other invited guests from both Germany and China. The participant’s interests ranged from various areas related to social computing research: computer science, statistics, physics, economics and business management, sociology, socio-psychology, communication sciences, and medical science/public health. Prof. Dr. Xiaoming Fu of the Institute of Computer Science, University of Göttingen, served as Symposium Co-Chair, together with Prof. Dr. Wenzhong Li from Nanjing University, China.
The technical programme of the symposium comprised 9 technical sessions with more than 30 research presentations, a poster session, two brainstorming sessions, and one day of lab visits and peer-to-peer discussions. Besides, Prof. Dr. John Mohr (University of California, Santa Barbara, USA), Prof. Dr. Peter Gloor (Massachusetts Institute of Technology, USA) and Prof. Dr. Sophie Mützel (U. Luzern, Switzerland) gave three keynote talks, sharing their experiences and visions on interdisciplinary social computing research. In addition, 8 researchers presented their work at the lively poster session, focusing on datasets and empirical social network analyses. During the last days, two special brainstorming sessions provided the researchers with the opportunity to identify potential collaborations, raising intimate and constructive discussions on the theme of big data and social networks.
