From divergence to convergence: How human–bot collaboration influences the evolution of collective knowledge in online knowledge communities

Abstract

Human–bot collaborative knowledge building is increasingly prevalent in online knowledge communities (OKCs). However, it is unclear how human and bot individual activities and their collaboration influence different stages of collective knowledge evolution. Based on a dataset of 337,830 edit and talk records sampled from 200 randomly selected Wikipedia articles, we first conducted an exploratory analysis to examine how the frequency of human and bot activities and the “frequency–breadth–depth” of their collaboration patterns change across stages of collective knowledge evolution. Furthermore, we utilized a fixed-effect multinomial logistic model to assess the effects of these variables on the stages of collective knowledge evolution. The results indicate the distinct impacts of human/bot activities and human–bot collaboration patterns on idea generating, idea organizing, and intellectual convergence. The core findings include (1) human activities promote idea generating and organizing, whereas bot activities facilitate idea organizing; (2) human-led collaboration patterns enhance idea generating and organizing, while co-led collaboration patterns promote intellectual convergence. These findings contribute to information science and human–bot collaboration research, as well as guide platform design and community administration of OKCs. Specifically, we recommend the implementation of stagedependent bot deployment strategies and human–bot collaboration incentives that align with the stages of collective knowledge evolution.