Measuring self-focus bias in community-maintained knowledge repositories

Brent Hecht; Darren Gergle

doi:10.1145/1556460.1556463

Measuring self-focus bias in community-maintained knowledge repositories

Brent Hecht, Darren Gergle

Communication Studies

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

80 Scopus citations

Abstract

Self-focus is a novel way of understanding a type of bias in community-maintained Web 2.0 graph structures. It goes beyond previous measures of topical coverage bias by encapsulating both node- and edge-hosted biases in a single holistic measure of an entire community-maintained graph. We outline two methods to quantify self-focus, one of which is very computationally inexpensive, and present empirical evidence for the existence of self-focus using a "hyperlingual"approach that examines 15 different language editions of Wikipedia. We suggest applications of our methods and discuss the risks of ignoring self-focus bias in technological applications.

Original language	English (US)
Title of host publication	C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies
Publisher	Association for Computing Machinery
Pages	11-19
Number of pages	9
ISBN (Print)	978-1605587134
DOIs	https://doi.org/10.1145/1556460.1556463
State	Published - 2009
Event	4th International Conference on Communities and Technologies, C and T 2009 - University Park, PA, United States Duration: Jun 25 2009 → Jun 27 2009

Publication series

Name	C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies
Volume	2009-January

Conference

Conference	4th International Conference on Communities and Technologies, C and T 2009
Country/Territory	United States
City	University Park, PA
Period	6/25/09 → 6/27/09

Funding

This research was funded, in part, by National Science Foundation grant #0705901 and Microsoft Research. A particularly special and grand thank you to Nada Petrović for all of her in-depth and valuable comments. Thanks also go out to Brian Keegan and Emily Moxley for their wise input on this paper and to our reviewers for their valuable comments.

Keywords

Self-focus
Web 2.0
Wikipedia
bias
hyperlingual
semantic networks
topical coverage

ASJC Scopus subject areas

Computer Networks and Communications

Access to Document

10.1145/1556460.1556463

Cite this

Hecht, B., & Gergle, D. (2009). Measuring self-focus bias in community-maintained knowledge repositories. In C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies (pp. 11-19). (C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies; Vol. 2009-January). Association for Computing Machinery. https://doi.org/10.1145/1556460.1556463

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Hecht, B & Gergle, D 2009, Measuring self-focus bias in community-maintained knowledge repositories. in C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies. C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies, vol. 2009-January, Association for Computing Machinery, pp. 11-19, 4th International Conference on Communities and Technologies, C and T 2009, University Park, PA, United States, 6/25/09. https://doi.org/10.1145/1556460.1556463

Measuring self-focus bias in community-maintained knowledge repositories. / Hecht, Brent; Gergle, Darren.
C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies. Association for Computing Machinery, 2009. p. 11-19 (C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies; Vol. 2009-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Hecht B, Gergle D. Measuring self-focus bias in community-maintained knowledge repositories. In C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies. Association for Computing Machinery. 2009. p. 11-19. (C and T 2009 - Proceedings of the 4th International Conference on Communities and Technologies). doi: 10.1145/1556460.1556463

Measuring self-focus bias in community-maintained knowledge repositories

Abstract

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Keywords

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