I read the summary of the VE study, and I have a question. Anecdotally, I am hearing from multiple sources that new editors *who attend workshops or editathons in person* prefer VE over wikitext for ease of use. Do we have any data specifically about the productivity and longevity of this population of users when they are introduced to to Wikipedia editing on VE instead of wikitext?
Thanks! Pine On Jul 29, 2015 11:09 AM, "Leila Zia" <[email protected]> wrote: > A friendly reminder that this is happening in 23 min. :-) > > YouTube stream: https://www.youtube.com/watch?v=vGyrVg_qKSM > IRC: #wikimedia-research > > Best, > Leila > > On Mon, Jul 27, 2015 at 2:47 PM, Leila Zia <[email protected]> wrote: > >> Hi everyone, >> >> The next Research showcase will be live-streamed this Wednesday, July 29 >> at 11.30 PT. The streaming link will be posted on the lists a few minutes >> before the showcase starts (sorry, we haven't been able to solve this, yet. >> :-() and as usual, you can join the conversation on IRC at #wikimedia >> -research. >> >> We look forward to seeing you! >> >> Leila >> >> >> This month: >> *VisualEditor's effect on newly registered users*By *Aaron Halfaker* >> <https://www.mediawiki.org/wiki/User:Halfak_%28WMF%29> >> >> It's been nearly two years since we ran an initial study >> <https://meta.wikimedia.org/wiki/Research:VisualEditor%27s_effect_on_newly_registered_editors/June_2013_study> >> of VisualEditor's effect on newly registered editors. While most of the >> results of this study were positive (e.g. workload on Wikipedians did >> not increase), we still saw a significant decrease in the newcomer >> productivity. In the meantime, the Editing >> <https://www.mediawiki.org/wiki/Editing> team has made substantial >> improvements to performance and functionality. In this presentation, I'll >> report on the results of a new experiment designed to test the effects of >> enabling this improved VisualEditor software for newly registered users >> by default. I'll show what we learned from the experiment and discuss some >> results have opened larger questions about what, exactly, is difficult >> about being a newcomer to English Wikipedia. >> >> *Wikipedia knowledge graph with DeepDive* >> By *Juhana Kangaspunta* and >> *Thomas Palomares (10-week student project)* >> Despite the tremendous amount of information present on Wikipedia, only >> a very little amount is structured. Most of the information is embedded in >> text and extracting it is a non-trivial challenge. In this project, we try >> to populate Wikidata, a structured component of Wikipedia, using DeepDive >> tool to extract relations embedded in the text. We finally extracted more >> than 140,000 relations with more than 90% average precision. We will >> present DeepDive and the data that we use for this project, we explain >> the relations we focused on so far and explain the implementation and >> pipeline, including our model, features and extractors. Finally, we detail >> our results with a thorough precision and recall analysis. >> > > > _______________________________________________ > Wiki-research-l mailing list > [email protected] > https://lists.wikimedia.org/mailman/listinfo/wiki-research-l > >
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