Chinese collaboration network data recompiled based on weights and labels. (2017) - Xing, Fan; Zhou, Chengbing; Suo, Xiafei; Ma, Tinghuai; Jin, Yuanfeng
The increasing popularity of social networks, such as online communities and collaboration networks, has given rise to interesting knowledge discovery and data mining problems. Different methods of knowledge discovery and data mining require different types of social network datasets, such as datasets including node and edge information or datasets with added labels or weights. In this paper, we review social network datasets in different formats and applications. Then, we propose a data processing method to add weights and labels for a Chinese collaboration network (C-DBLP). The weights reflect the affinity between two authors, and the labels contain information about the authors. This dataset can be used for privacy protection in social networks and social network community detection. Finally, we analyse the new data that we compiled and draw conclusions about the importance of the weights in the C-DBLP dataset in terms of social network research.