We study collaboration patterns of Wikidata, one of the world's largest collaborative knowledge graph communities. Wikidata lacks long-term engagement with a small group of priceless members, 0.8%, to be responsible for 80% of contributions. Therefore, it is essential to investigate their behavioural patterns and find ways to enhance their contributions and participation. Previous studies have highlighted the importance of discussions among contributors in understanding these patterns. To investigate this, we analyzed all the discussions on Wikidata and used a mixed methods approach, including statistical tests, network analysis, and text and graph embedding representations. Our research showed that the interactions between Wikidata editors form a small world network where the content of a post influences the continuity of conversations. We also found that the account age of Wikidata members and their conversations are significant factors in their long-term engagement with the project. Our findings can benefit the Wikidata community by helping them improve their practices to increase contributions and enhance long-term participation.

翻译：本研究探讨了维基数据——全球规模最大的协作知识图谱社区之一——的协作模式。维基数据长期面临核心成员参与不足的挑战，仅占成员总数0.8%的贡献者承担了80%的内容编辑工作。因此，深入解析核心贡献者的行为模式并探索提升其贡献度与参与度的途径至关重要。既有研究指出，贡献者间的讨论对理解此类行为模式具有关键意义。为此，我们采用混合研究方法——包括统计检验、网络分析以及文本与图嵌入表征技术——对维基数据平台的全部讨论记录进行了系统性分析。研究发现：维基数据编辑者间的互动形成了小世界网络结构，且讨论帖的内容质量直接影响对话的持续深度；同时，成员账户存续时长及其参与讨论的频率是预测其长期项目参与度的显著影响因素。本研究成果可为维基数据社区优化协作实践提供理论依据，助力提升整体贡献水平并强化长期参与机制。