Abstract: Firstly, the internet environment in the era of big data where the crowds interact adequately each other was analyzed. Secondly, the concept of web collective intelligence was put forward and explained, and its characteristics involving network data driven, complex interaction form, strong network effect, knowledge production dominated and cognition with uncertainty were obtained, then the research paradigm of web collective intelligence was put forward, the method with complexity science methodology as the guidance adheres to syncretism, took complexity science, networked data mining and artificial intelligence with uncertainty as backbone theory and method, outstood web collective intelligence characteristic and interdisciplinary research, and applied a technique with a combination of system analysis, modeling analysis and simulation analysis to study the scientific problems of web collective intelligence from multiscale and multilevel perspective, which solves the deficiency problem of the research theories and methods of web collective intelligence and deepens the knowledge of web collective intelligence and social computing.
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Key words: big data, internet, web collective intelligence, complexity science, networked data mining, artificial intelligence with uncertainty
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