20251115-DTEHM_research data

Title: How Collective-Intelligence Collaboration Influences Resource Evolution in Open Networked Communities: Mechanisms and Evidence
This study was exploratory and was not pre-registered prior to data collection. This study, through a comprehensive literature review, explores the influence of group collaborative interactions on resource content evolution in the process of community-based learning. It focuses on three major categories of characteristics: contextual characteristics (topic type), group structural characteristics (group size and diversity), and interaction characteristics (interaction intensity and interaction depth). The findings from prior studies indicate that the characteristics influencing the evolution of high-quality resource content are diverse and complex. Given the inconsistencies in existing research conclusions, this study proposes the following preliminary hypotheses:
1)In topic-based community learning processes, certain characteristics may serve as key conditions influencing resource content evolution.
2)The quality of resource evolution in community learning is affected by the synergistic effects of multiple characteristics, and different combinations of these characteristics may lead to equivalent evolutionary pathways.
Based on these hypotheses, this study integrates Group Communication Analysis (GCA) and Discrete-Time Event History Analysis (DTEHA) to investigate the mechanisms through which collective collaboration in resource production promotes resource content evolution. Compared with traditional linear or static analytical approaches, this combined method captures both the dynamic communicative features of collaborative processes and the temporal patterns of resource change, thereby providing a more effective means of uncovering the sustained influence of group collaborative behaviors on resource evolution.