WikiIndaba conference 2018/Program/Growing Wikipedia Across Languages via Recommendation Systems

ID: Recommendation_systems	Growing Wikipedia Across Languages via Recommendation Systems
Speakers: Leila Zia (Wikimedia Foundation, United States)		Time block: saturday-morning	Start: 11:50
		Location: Great room	Duration: 40 min.
Description : Millions of articles are missing in Wikipedia across its more than 160 actively edited languages, and many of the articles that already exist have significant gaps of content. In English Wikipedia alone, only 1% of the more than 5 million articles have quality labels Good or better, 37% are stubs. I present the state of research in identifying missing Wikipedia articles across languages. I show how we have used data mining approaches to find what articles are missing in a given Wikipedia languages, prioritized them, and built systems that would recommend such missing articles to editors that are interested to contribute to them. I present the result of the experiment that showed we can triple article creation rate in French Wikipedia using the existing editor community and without compromising on article quality. I will present GapFinder , a tool that is designed to help interested editors find missing articles in their language based on their interests. I will present the more recent state of this research which was partly motivated by our conversations with The Africa Destubathon organizers in 2016. In this second part, I will show you how we can use the content and structure of a given Wikipedia language as well as other Wikipedia languages to find missing sections in an already existing Wikipedia article and recommend them to editors for article expansion. Lastly, I will talk with you about what we know about the needs of the readers of Wikipedia from northern Africa and Sub-Saharan Africa (ongoing documentation), what we do not know and we should embark on learning, and reflect on some of the issues around bias in content and how we should overcome them on our way to knowledge equity.			Themes: Wikimedia Research
			Tags: Growing Wikipedia, Recommendation systems, Reducing content gap
			Notes: #WikiIndaba18_Recommendation_systems