Recognizing contributions in wikis: Authorship categories, algorithms, and visualizations

  • Authors:

  • Ofer Arazy;Eleni Stroulia;Stan Ruecker;Cristina Arias;Carlos Fiorentino;Veselin Ganev;Timothy Yau

  • Affiliations:

  • Department of Accounting and Management Information Systems (AMIS) School of Business, University of Alberta, Edmonton, AB T6G 2E8 Canada;Computing Science Department, University of Alberta, Edmonton, AB T6G 2E8 Canada;Humanities Computing Program, Department of English and Film Studies and Office of Interdisciplinary Studies, University of Alberta, Edmonton, AB T6G 2E5 Canada;Humanities Computing Program, Office of Interdisciplinary Studies, University of Alberta, Edmonton, AB T6G 2E5 Canada;Department of Art and Design, University of Alberta, Edmonton, AB T6G 2C9 Canada;Computing Science Department, University of Alberta, Edmonton, AB T6G 2E8 Canada;Computing Science Department, University of Alberta, Edmonton, AB T6G 2E8 Canada

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2010

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Abstract

Wikis are designed to support collaborative editing, without focusing on individual contribution, such that it is not straightforward to determine who contributed to a specific page. However, as wikis are increasingly adopted in settings such as business, government, and education, where editors are largely driven by career goals, there is a perceived need to modify wikis so that each editor's contributions are clearly presented. In this paper we introduce an approach for assessing the contributions of wiki editors along several authorship categories, as well as a variety of information glyphs for visualizing this information. We report on three types of analysis: (a) assessing the accuracy of the algorithms, (b) estimating the understandability of the visualizations, and (c) exploring wiki editors' perceptions regarding the extent to which such an approach is likely to change their behavior. Our findings demonstrate that our proposed automated techniques can estimate fairly accurately the quantity of editors' contributions across various authorship categories, and that the visualizations we introduced can clearly convey this information to users. Moreover, our user study suggests that such tools are likely to change wiki editors' behavior. We discuss both the potential benefits and risks associated with solutions for estimating and visualizing wiki contributions. © 2010 Wiley Periodicals, Inc.