Research On The Influence Mechanism Of Human-bot Collaboration Performance In Online Community

With the development of Web2.0 technology,online communities(OC)have become an online self-organized platform for open collaboration.The emergence of Artificial Intelligence(AI)leads to the fact that collaboration activities can be solved by AI in OC,and the collaboration mechanism has shifted to human-bot collaboration.However,the existing research is still in the preliminary stage and the current field lacks a corresponding theoretical system.Besides,the influence mechanism of human-bot collaboration performance from the perspective of human-bot complementary augmentation is still not found.Therefore,this paper is researched in the context of Wikipedia which represents OC.Firstly,based on the coordination theory and the IPO model,the research model of human-bot collaboration performance of OC is constructed.Secondly,based on the α ++ algorithm and local process mining methods of process mining,the human-bot collaboration pattern mining model is constructed.Different types of human-bot collaboration patterns are mined from Wikipedia’s original log data.Thirdly,according to the research model and the complementary effect test method based on interaction terms,the influence mechanism of human-bot collaboration patterns and the human-bot complementary augmentation relationship are found.Finally,based on the research model,the influence mechanism of human-bot collaboration performance is found.Based on the above results,this paper discovers the influence mechanism of human-bot collaboration patterns and human-bot collaboration performance,reveals the formation mechanism of the human-bot collaboration patterns,and verifies the complementary augmentation relationship between humans and bots in OC.This paper provides corresponding management implication for OC,enriches the theory of human-bot collaboration and the research of OC,and provides a basis for future research of human-bot collaboration in OC.