Formation Mechanism of Human-Bot Collaboration Pat-terns in Knowledge Society Construction within Online Knowledge Community:A Perspective on Human-Bot Complementarity
With the development of AI,Online Knowledge Communi-ties(OKCs)are becoming important platforms for the co-construction of knowledge by humans and bots.In the co-construction process,it requires humans and bots to leverage their respective strengths to com-plete tasks with varying degrees of complexity.The complementary of these strengths mitigates individual limitations,fostering a healthier community development.Therefore,it is crucial to explore how hu-mans and bots with different attributes can form efficient collaboration patterns based on their complementary relationship,especially for the social construction of knowledge within OKCs.Current research gap exists in exploring the formation mechanism of human-bot collaboration patterns in the process of knowledge social construction from the perspective of human-bot complementary.To ad-dress this gap,based on Social Constructivism Theory and Coordina-tion theory,this paper constructs a research framework for the forma-tion of the human-bot collaboration patterns from the microscopic hu-man-bot attributes,and uses process mining,Interaction effect testing and other methods to test the model hypotheses.The results show that:(1)The cognitive attributes of humans and the perceptual attributes of bots can facilitate the formation of different types of human-bot collab-oration patterns.In details,humans' cognition ability,bots' intelligence level and perception ability all promote the formation of sequential human-bot collaboration patterns,while humans' cognition structure plays a negative role;humans' knowledge structure and cognition abili-ty,bots' perception ability significantly promote the formation of cyclic human-bot collaboration patterns,while bots' intelligence level does not work;(2)in all types of human-bot collaboration patterns,there is an interaction relationship between the cognitive structure of humans and the perceptual capabilities of bots;(3)task complexity moderates the relationship between human-bot attributes and the formation of collaboration patterns.In both types of cyclic patterns,task complexity strengthens the influence of human knowledge structures on the for-mation of collaboration patterns,while weakening the relation of bots'intelligence level or perception ability.This study provides significant theoretical contributions and practical implications.Theoretically,this study explains the factors and mecha-nisms affecting collaboration patterns in knowledge construction sce-narios.It enriches the research on human-bot collaboration mechanisms within OKCs from the perspective of empirical research.Furthermore,by investigating the interaction effects based on human-bot attributes,it enriches the study of collaboration patterns within OKCs from the perspective of human-bot complementary.It expands the application of theories related to human-bot complementary in the field of OKC human-bot collaboration research.Practically,the study finds that the different attributes of humans and bots have a significant impact on the formation of collaboration pat-terns.These findings provide new management insights for human-bot knowledge construction on OKC.OKC can encourage users to update their knowledge structures through learning.This enables them to con-tribute more novel knowledge in the process of individual knowledge construction,thereby facilitating the generation of collective wisdom within the community.Besides,OKC can promote the development of more intelligent and perceptive bots.These bots can collaborate more effectively to complete knowledge construction tasks.Additionally,the study reveals a complementary relationship between human and bot attributes.It also finds that task complexity influences the impact of these attributes on human-bot collaboration patterns.Accordingly,measures can be developed to optimize the makeup of human-robot teams so that OKC can then recommend suitable tasks based on the distinct attributes of humans and bots.
Online Knowledge CommunityKnowledge Society Con-structionHuman-Bot Collaboration PatternHuman-Bot Interaction
万方数据
