Time correction: The next Research Showcase will be live-streamed next Wednesday, June 26, at *11:30 AM PDT/18:30 UTC*.
On Mon, Jun 24, 2019 at 4:11 PM Janna Layton <[email protected]> wrote: > Hi all, > > The next Research Showcase will be live-streamed this Wednesday, June 26, > at 11:30 AM PST/19:30 UTC. We will have three presentations this showcase, > all relating to Wikipedia blocks. > > YouTube stream: https://www.youtube.com/watch?v=WiUfpmeJG7E > > As usual, you can join the conversation on IRC at #wikimedia-research. You > can also watch our past research showcases here: > https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase > > This month's presentations: > > Trajectories of Blocked Community Members: Redemption, Recidivism and > Departure > > By Jonathan Chang, Cornell University > > Community norm violations can impair constructive communication and > collaboration online. As a defense mechanism, community moderators often > address such transgressions by temporarily blocking the perpetrator. Such > actions, however, come with the cost of potentially alienating community > members. Given this tradeoff, it is essential to understand to what extent, > and in which situations, this common moderation practice is effective in > reinforcing community rules. In this work, we introduce a computational > framework for studying the future behavior of blocked users on Wikipedia. > After their block expires, they can take several distinct paths: they can > reform and adhere to the rules, but they can also recidivate, or > straight-out abandon the community. We reveal that these trajectories are > tied to factors rooted both in the characteristics of the blocked > individual and in whether they perceived the block to be fair and > justified. Based on these insights, we formulate a series of prediction > tasks aiming to determine which of these paths a user is likely to take > after being blocked for their first offense, and demonstrate the > feasibility of these new tasks. Overall, this work builds towards a more > nuanced approach to moderation by highlighting the tradeoffs that are in > play. > > > Automatic Detection of Online Abuse in Wikipedia > > By Lane Rasberry, University of Virginia > > Researchers analyzed all English Wikipedia blocks prior to 2018 using > machine learning. With insights gained, the researchers examined all > English Wikipedia users who are not blocked against the identified > characteristics of blocked users. The results were a ranked set of > predictions of users who are not blocked, but who have a history of conduct > similar to that of blocked users. This research and process models a system > for the use of computing to aid human moderators in identifying conduct on > English Wikipedia which merits a block. > > Project page: > https://meta.wikimedia.org/wiki/University_of_Virginia/Automatic_Detection_of_Online_Abuse > > Video: https://www.youtube.com/watch?v=AIhdb4-hKBo > > > First Insights from Partial Blocks in Wikimedia Wikis > > By Morten Warncke-Wang, Wikimedia Foundation > > The Anti-Harassment Tools team at the Wikimedia Foundation released the > partial block feature in early 2019. Where previously blocks on Wikimedia > wikis were sitewide (users were blocked from editing an entire wiki), > partial blocks makes it possible to block users from editing specific pages > and/or namespaces. The Italian Wikipedia was the first wiki to start using > this feature, and it has since been rolled out to other wikis as well. In > this presentation, we will look at how this feature has been used in the > first few months since release. > > > -- > Janna Layton (she, her) > Administrative Assistant - Audiences & Technology > Wikimedia Foundation <https://wikimediafoundation.org/> > -- Janna Layton (she, her) Administrative Assistant - Audiences & Technology Wikimedia Foundation <https://wikimediafoundation.org/>
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