Maciel Zortea, Miguel Paredes, et al.
IGARSS 2021
The article focuses on data mining technologies for computational social science. The emergence of online social network sites and web 2.0 applications generate a large volume of valuable data. This greatly stimulates the development of computational social science, which tries to solve the research problems in traditional social science with the help of computational technologies. In addition to novel computational models, it would also be interesting to see the application of data mining techniques in real social problems. With the burst of various online social network, people are also interested in mining the people emotions from those online data. There are many fundamental problems in social sciences, such as detecting underlying communities, analyzing the mechanism of a specific behavior (social activity) and discovering the evolutionary patterns in a community.
Maciel Zortea, Miguel Paredes, et al.
IGARSS 2021
Yvonne Anne Pignolet, Stefan Schmid, et al.
Discrete Mathematics and Theoretical Computer Science
Daniel M. Bikel, Vittorio Castelli
ACL 2008
Matthias Kaiserswerth
IEEE/ACM Transactions on Networking