Omnipedia: Bridging the Wikipedia language gap

Patti Bao, Brent Hecht, Samuel Carton, Mahmood Quaderi, Michael Horn, Darren Gergle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

52 Scopus citations

Abstract

We present Omnipedia, a system that allows Wikipedia readers to gain insight from up to 25 language editions of Wikipedia simultaneously. Omnipedia highlights the similarities and differences that exist among Wikipedia language editions, and makes salient information that is unique to each language as well as that which is shared more widely. We detail solutions to numerous front-end and algorithmic challenges inherent to providing users with a multilingual Wikipedia experience. These include visualizing content in a language-neutral way and aligning data in the face of diverse information organization strategies. We present a study of Omnipedia that characterizes how people interact with information using a multilingual lens. We found that users actively sought information exclusive to unfamiliar language editions and strategically compared how language editions defined concepts. Finally, we briefly discuss how Omnipedia generalizes to other domains facing language barriers.

Original languageEnglish (US)
Title of host publicationConference Proceedings - The 30th ACM Conference on Human Factors in Computing Systems, CHI 2012
Pages1075-1084
Number of pages10
DOIs
StatePublished - May 24 2012
Event30th ACM Conference on Human Factors in Computing Systems, CHI 2012 - Austin, TX, United States
Duration: May 5 2012May 10 2012

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Other

Other30th ACM Conference on Human Factors in Computing Systems, CHI 2012
CountryUnited States
CityAustin, TX
Period5/5/125/10/12

Keywords

  • Hyperlingual
  • Language barrier
  • Multilingual
  • Text mining
  • User-generated content
  • Wikipedia

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