IEEE ACCESS SPECIAL SECTION EDITORIAL: ADVANCED DATA MINING METHODS FOR SOCIAL COMPUTING

Yongqiang Zhao

doi:10.1109/ACCESS.2020.3043060

IEEE ACCESS SPECIAL SECTION EDITORIAL: ADVANCED DATA MINING METHODS FOR SOCIAL COMPUTING

2020-01-01

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Yongqiang Zhao *

Shirui Pan (Shirui Pan)

DOI：10.1109/ACCESS.2020.3043060

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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.

IEEE ACCESS SPECIAL SECTION EDITORIAL: ADVANCED DATA MINING METHODS FOR SOCIAL COMPUTING

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