Abstract
Various kinds of social networks develop explosively, such as online social networks, scientific cooperation networks, athlete networks, airport passage networks, and so on. With the large number of participants and real-time property, social networks increasingly demonstrate their strength in information dissemination. Social computing has become a promising research area and attracts lots of attention. Analyzing and mining human behaviors, topological structure, and information diffusion in social networks can help to understand the essential mechanism of macroscopic phenomena, discover potential public interest, and provide early warnings of collective emergencies.
Highlights
Various kinds of social networks develop explosively, such as online social networks, scientific cooperation networks, athlete networks, airport passage networks, and so on
Analyzing and mining human behaviors, topological structure, and information diffusion in social networks can help to understand the essential mechanism of macroscopic phenomena, discover potential public interest, and provide early warnings of collective emergencies
Advanced multidisciplinary data collection and data mining methods should be proposed for social computing and developed to study social networks
Summary
Various kinds of social networks develop explosively, such as online social networks, scientific cooperation networks, athlete networks, airport passage networks, and so on. IEEE ACCESS SPECIAL SECTION EDITORIAL: ADVANCED DATA MINING METHODS FOR SOCIAL COMPUTING
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