Talking Wikidata: Communication patterns and their impact on community engagement in collaborative knowledge graphs

Fuente: arXiv
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Main Authors: Koutsiana, Elisavet, Reklos, Ioannis, Alghamdi, Kholoud Saad, Jain, Nitisha, Meroño-Peñuela, Albert, Simperl, Elena
Format: Preprint
Published: 2024
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author Koutsiana, Elisavet
Reklos, Ioannis
Alghamdi, Kholoud Saad
Jain, Nitisha
Meroño-Peñuela, Albert
Simperl, Elena
author_facet Koutsiana, Elisavet
Reklos, Ioannis
Alghamdi, Kholoud Saad
Jain, Nitisha
Meroño-Peñuela, Albert
Simperl, Elena
contents We study collaboration patterns of Wikidata, one of the world's largest open source collaborative knowledge graph (KG) communities. Collaborative KG communities, play a key role in structuring machine-readable knowledge to support AI systems like conversational agents. However, these communities face challenges related to long-term member engagement, as a small subset of contributors often is responsible for the majority of contributions and decision-making. While prior research has explored contributors' roles and lifespans, discussions within collaborative KG communities remain understudied. To fill this gap, we investigated the behavioural patterns of contributors and factors affecting their communication and participation. We analysed all the discussions on Wikidata using a mixed methods approach, including statistical tests, network analysis, and text and graph embedding representations. Our findings reveal that the interactions between Wikidata editors form a small world network, resilient to dropouts and inclusive, where both the network topology and discussion content influence the continuity of conversations. Furthermore, the account age of Wikidata members and their conversations are significant factors in their long-term engagement with the project. Our observations and recommendations can benefit the Wikidata and semantic web communities, providing guidance on how to improve collaborative environments for sustainability, growth, and quality.
format Preprint
id arxiv_https___arxiv_org_abs_2407_18278
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Talking Wikidata: Communication patterns and their impact on community engagement in collaborative knowledge graphs
Koutsiana, Elisavet
Reklos, Ioannis
Alghamdi, Kholoud Saad
Jain, Nitisha
Meroño-Peñuela, Albert
Simperl, Elena
Social and Information Networks
Human-Computer Interaction
We study collaboration patterns of Wikidata, one of the world's largest open source collaborative knowledge graph (KG) communities. Collaborative KG communities, play a key role in structuring machine-readable knowledge to support AI systems like conversational agents. However, these communities face challenges related to long-term member engagement, as a small subset of contributors often is responsible for the majority of contributions and decision-making. While prior research has explored contributors' roles and lifespans, discussions within collaborative KG communities remain understudied. To fill this gap, we investigated the behavioural patterns of contributors and factors affecting their communication and participation. We analysed all the discussions on Wikidata using a mixed methods approach, including statistical tests, network analysis, and text and graph embedding representations. Our findings reveal that the interactions between Wikidata editors form a small world network, resilient to dropouts and inclusive, where both the network topology and discussion content influence the continuity of conversations. Furthermore, the account age of Wikidata members and their conversations are significant factors in their long-term engagement with the project. Our observations and recommendations can benefit the Wikidata and semantic web communities, providing guidance on how to improve collaborative environments for sustainability, growth, and quality.
title Talking Wikidata: Communication patterns and their impact on community engagement in collaborative knowledge graphs
topic Social and Information Networks
Human-Computer Interaction
url https://arxiv.org/abs/2407.18278