TY - JOUR
T1 - Relating Wikipedia article quality to edit behavior and link structure
AU - Ruprechter, Thorsten
AU - Santos, Tiago
AU - Helic, Denis
PY - 2020/12/1
Y1 - 2020/12/1
N2 - Currently, the relation between edit behavior, link structure, and article quality is not well-understood in our community, notwithstanding that this relationship may facilitate editing processes and content quality on Wikipedia. To shed light on this complex relation, we classify article edits and perform an in-depth analysis of editing sequences for 4941 articles. Additionally, we build a network of internal Wikipedia hyperlinks between articles. Using this data, we compute parsimonious metrics to quantify editing and linking behavior. Our analysis unveils that conflicted articles differ substantially from others in almost all metrics, while we also detect slight trends for high-quality articles. With our network analysis we find evidence indicating that controversial and edit war articles frequently span structural holes in the Wikipedia network. Finally, in a prediction experiment we demonstrate the usefulness of edit behavior patterns and network properties in predicting conflict and article quality. With our work, we assist online collaboration communities, especially Wikipedia, in long-term improvement of content quality by offering valuable insights about the interplay of article quality, controversies and edit wars, editing behavior, and network properties via sequence-based edit and network-based article metrics.
AB - Currently, the relation between edit behavior, link structure, and article quality is not well-understood in our community, notwithstanding that this relationship may facilitate editing processes and content quality on Wikipedia. To shed light on this complex relation, we classify article edits and perform an in-depth analysis of editing sequences for 4941 articles. Additionally, we build a network of internal Wikipedia hyperlinks between articles. Using this data, we compute parsimonious metrics to quantify editing and linking behavior. Our analysis unveils that conflicted articles differ substantially from others in almost all metrics, while we also detect slight trends for high-quality articles. With our network analysis we find evidence indicating that controversial and edit war articles frequently span structural holes in the Wikipedia network. Finally, in a prediction experiment we demonstrate the usefulness of edit behavior patterns and network properties in predicting conflict and article quality. With our work, we assist online collaboration communities, especially Wikipedia, in long-term improvement of content quality by offering valuable insights about the interplay of article quality, controversies and edit wars, editing behavior, and network properties via sequence-based edit and network-based article metrics.
KW - Article quality
KW - Conflict
KW - Controversy
KW - Edit behavior
KW - Edit wars
KW - Link structure
KW - Semantic edit types
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=85090394298&partnerID=8YFLogxK
U2 - 10.1007/s41109-020-00305-y
DO - 10.1007/s41109-020-00305-y
M3 - Article
AN - SCOPUS:85090394298
SN - 2364-8228
VL - 5
JO - Applied Network Science
JF - Applied Network Science
IS - 1
M1 - 61
ER -