Wikipedia:Wikipedia Signpost/2019-06-30/Recent research

A monthly overview of recent academic research about Wikipedia and other Wikimedia projects, also published as the Wikimedia Research Newsletter.

Reviewed by FULBERT

In Chang and Danescu-Niculescu-Mizil’s study "Trajectories of Blocked Community Members: Redemption, Recidivism and Departure", presented at The Web Conference last month, the authors explored the effectiveness of temporary editor blocks imposed as acts of moderation for inappropriate conduct on Wikipedia. The researchers wanted to understand how effective these blocks were as a tool intended to reform editors whose online conduct was problematic enough to warrant discipline, but not so egregious as to impose an indefinite block, i.e. where there was hope that this action may help reform the editors who demonstrate evidence they can be productive ongoing contributors to Wikipedia.

The researchers limited their study to the first block received by users, beginning with a total sample of 104,245 blocks over the history of English Wikipedia. They focused on four types of blocks that enforced community norms — personal attacks and incivility, harassment, edit warring, and disruptive editing — arriving at a dataset comprising 6,026 blocked users. They were particularly interested in editor departure, which they defined as the time of the last comment a user makes on community talk pages, in part because they focused their attention on community engagement. Likewise, they explored recidivism, which is when a previously-blocked user is blocked again for any additional breach of community rules, compared to those who reform and are never blocked again.

They found that "users are much more likely to depart if they were blocked before, especially in the first months of their life in the community (p. 4)”. Indeed, users are more likely to depart during the month of their block, and this is compounded by the finding that users who were blocked a first time had an increased probability of being blocked again. These findings were impacted by the length of time one was an active member of the user community, where the greater the length of one's involvement, the less likely blocks were to occur, especially through recidivism. The authors then explored user activity level and activity spread, learning that recidivist users engage in interaction with members of the community with more depth than breadth, involving a smaller set of users while continuing more prolonged engagement. Finally, the researchers explored blocked users' perception of fairness, focused through blockage appeals. Those who apologized for their infractions were less likely to suffer from recidivism, while those who directly questioned their blocks or claimed a lack of fairness instead faced a moderate increase in recidivism.

The authors concluded that working toward a "more nuanced approach to moderation that more broadly accounts for the tradeoffs between possible outcomes and that considers how the affected individuals might perceive the moderators and their actions (p. 10)” is something that should be considered when moderators (administrators) consider blocking users for transgressions to community standards.

See the research events page on Meta-wiki for upcoming conferences and events, including submission deadlines, and the page of the monthly Wikimedia Research Showcase for videos and slides of past presentations.

Other recent publications that could not be covered in time for this issue include the items listed below. Contributions, whether reviewing or summarizing newly published research, are always welcome.

Compiled by Tilman Bayer

From the abstract:

From the abstract and paper:

An earlier, related preprint by some of the same authors was covered by Technology Review under the headline "Wikipedia-Mining Algorithm Reveals World’s Most Influential Universities".

From the abstract and paper:

The various resulting rankings place e.g. "University of Cambridge" 2nd (after "human") by degree centrality in the article network for "computer science", and "C (programming language)" 2nd by closeness centrality in the article network for "programming language" (after "programming language" itself).

From the abstract:

From the abstract:

The resulting ranking is lead by lung cancer, breast cancer and leukemia.

See also earlier coverage of a related paper by the same authors: "World Influence of Infectious Diseases from Wikipedia Network Analysis"

From the abstract:

See also OpenReview discussion

From the abstract:

From the abstract:

From the abstract:

From the abstract:

From the abstract:

From the abstract: