Omnipedia: bridging the wikipedia language gap

  • Authors:
  • Patti Bao;Brent Hecht;Samuel Carton;Mahmood Quaderi;Michael Horn;Darren Gergle

  • Affiliations:
  • Northwestern University, Evanston, Illinois, United States;Northwestern University, Evanston, Illinois, United States;Northwestern University, Evanston, Illinois, United States;Northwestern University, Evanston, Illinois, United States;Northwestern University, Chicago, Illinois, United States;Northwestern University, Evanston, Illinois, United States

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2012

Quantified Score

Hi-index 0.01

Visualization

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.