Talking Wikidata: Communication patterns and their impact on community engagement in collaborative knowledge graphs
<|reference_start|>Talking Wikidata: Communication patterns and their impact on community engagement in collaborative knowledge graphs: 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.<|reference_end|>
@article{koutsiana2024talking,
    title={Talking Wikidata: Communication patterns and their impact on community
  engagement in collaborative knowledge graphs},
    author={Elisavet Koutsiana, Ioannis Reklos, Kholoud Saad Alghamdi, Nitisha
  Jain, Albert Mero~no-Pe~nuela, Elena Simperl},
    journal={arXiv preprint arXiv:2407.18278},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.18278},
    primaryClass={cs.SI cs.HC}
}