Hi everyone,
The next Research Showcase will be live-streamed on Wednesday, March 20, at 9:30 AM PST / 16:30 UTC. Find your local time here https://zonestamp.toolforge.org/1710952200. In line with Women's History Month, the theme for this showcase is *Addressing Knowledge Gaps*.
You are welcome to watch via the YouTube stream: https://www.youtube.com/watch?v=D6wrr9WShTk. As usual, you can join the conversation in the YouTube chat as soon as the showcase goes live.
This month's presentation: Leveraging Recommender Systems to Reduce Content Gaps on WikipediaBy *Mo Houtti*Many Wikipedians use algorithmic recommender systems to help them find interesting articles to edit. The algorithms underlying those systems are driven by a straightforward assumption: we can look at what someone edited in the past to figure out what they’ll most likely want to edit next. But the story of what Wikipedians want to edit is almost definitely more complex than that. For example, our own prior research shows that Wikipedians prefer prioritizing articles that would minimize content gaps. So, we asked, what would happen if we incorporated that value into Wikipedians’ personalized recommendations? Through a controlled experiment on SuggestBot, we found that recommending more content gap articles didn’t significantly impact editing, despite those articles being less “optimally interesting” according to the recommendation algorithm. In this presentation, I will describe our experiment, our results, and their implications - including how recommender systems can be one useful strategy for tackling content gaps on Wikipedia.Bridging the offline and online- Offline meetings of WikipediansBy *Nicole Schwitter*Wikipedia is primarily known as an online encyclopaedia, but it also features a noteworthy offline component: Wikipedia and particularly its German-language edition – which is one of the largest and most active language versions – is characterised by regular local offline meetups which give editors the chance to get to know each other. This talk will present the recently published dewiki meetup dataset which covers (almost) all offline gatherings organised on the German-language version of Wikipedia. The dataset covers almost 20 years of offline activity of the German-language Wikipedia, containing 4418 meetups that have been organised with information on attendees, apologies, date and place of meeting, and minutes recorded. The talk will explain how the dataset can be used for research, highlight the importance of considering offline meetings among Wikipedians, and place these insights within the context of addressing gender gaps within Wikipedia.
Best,
Kinneret
Hello all,
Quick reminder that we will be starting in less than an hour. Join us at https://www.youtube.com/watch?v=D6wrr9WShTk.
On Fri, Mar 15, 2024 at 6:19 PM Kinneret Gordon kgordon@wikimedia.org wrote:
Hi everyone,
The next Research Showcase will be live-streamed on Wednesday, March 20, at 9:30 AM PST / 16:30 UTC. Find your local time here https://zonestamp.toolforge.org/1710952200. In line with Women's History Month, the theme for this showcase is *Addressing Knowledge Gaps*.
You are welcome to watch via the YouTube stream: https://www.youtube.com/watch?v=D6wrr9WShTk. As usual, you can join the conversation in the YouTube chat as soon as the showcase goes live.
This month's presentation: Leveraging Recommender Systems to Reduce Content Gaps on WikipediaBy *Mo Houtti*Many Wikipedians use algorithmic recommender systems to help them find interesting articles to edit. The algorithms underlying those systems are driven by a straightforward assumption: we can look at what someone edited in the past to figure out what they’ll most likely want to edit next. But the story of what Wikipedians want to edit is almost definitely more complex than that. For example, our own prior research shows that Wikipedians prefer prioritizing articles that would minimize content gaps. So, we asked, what would happen if we incorporated that value into Wikipedians’ personalized recommendations? Through a controlled experiment on SuggestBot, we found that recommending more content gap articles didn’t significantly impact editing, despite those articles being less “optimally interesting” according to the recommendation algorithm. In this presentation, I will describe our experiment, our results, and their implications - including how recommender systems can be one useful strategy for tackling content gaps on Wikipedia.Bridging the offline and online- Offline meetings of WikipediansBy *Nicole Schwitter*Wikipedia is primarily known as an online encyclopaedia, but it also features a noteworthy offline component: Wikipedia and particularly its German-language edition – which is one of the largest and most active language versions – is characterised by regular local offline meetups which give editors the chance to get to know each other. This talk will present the recently published dewiki meetup dataset which covers (almost) all offline gatherings organised on the German-language version of Wikipedia. The dataset covers almost 20 years of offline activity of the German-language Wikipedia, containing 4418 meetups that have been organised with information on attendees, apologies, date and place of meeting, and minutes recorded. The talk will explain how the dataset can be used for research, highlight the importance of considering offline meetings among Wikipedians, and place these insights within the context of addressing gender gaps within Wikipedia.
Best,
Kinneret
--
Kinneret Gordon
Lead Research Community Officer
Wikimedia Foundation https://wikimediafoundation.org/