Through a glass darkly: Information technology design, identity verification, and knowledge contribution in online communities
Abstract
A variety of information technology (IT) artifacts, such as those supporting reputation management and digital archives of past interactions, are commonly deployed to support online communities. Despite their ubiquity, theoretical and empirical research investigating the impact of such IT-based features on online community communication and interaction is limited. Drawing on the social psychology literature, we describe an identity-based view to understand how the use of IT-based features in online communities is associated with online knowledge contribution. Specifically, the use of four categories of IT artifacts—those supporting virtual co-presence, persistent labeling, self-presentation, and deep profiling—is proposed to enhance perceived identity verification, which thereafter promotes satisfaction and knowledge contribution. To test the theoretical model, we surveyed more than 650 members of two online communities. In addition to the positive effects of community IT artifacts on perceived identity verification, we also find that perceived identity verification is strongly linked to member satisfaction and knowledge contribution. This paper offers a new perspective on the mechanisms through which IT features facilitate computer-mediated knowledge sharing, and it yields important implications for the design of the supporting IT infrastructure.
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Mutual understanding among members, group attachment, and identification are crucial for online community success.
“Mutual understanding among members (Ma & Agarwal, 2007) as well as group attachment and identification (Panteli & Sivunen, 2019;Ren, Kraut, & Kiesler, 2007) have been found to be crucial for OC success.”
From Climate change and COP26: Are digital technologies and information management part of the problem or the solution? An editorial reflection and call to action (2022) · cites this paper as Ma & Agarwal, 2007
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- Authors
- Ma, M., & Agarwal, R.
- Affiliations
- University of Maryland, College Park (US)
- Venue
- Information Systems Research
- Published
- 2007-03
- Volume
- 18
- Issue
- 1
- Pages
- 42-67
- ISSN
- 1047-7047 (ISSN-L)
- 1526-5536
- OpenAlex
- W2165117260
- Cited by
- 1,143
- References
- 165
- Citations by year
- 2026: 25 · 2025: 26 · 2024: 41 · 2023: 52 · 2022: 60 · 2021: 62 · 2020: 66 · 2019: 61 · 2018: 55 · 2017: 54 · 2016: 75 · 2015: 89 · 2014: 90 · 2013: 91 · 2012: 75
- FWCI
- 191.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Information Systems Research (publishedVersion)
- Topics
- Social Sciences › Communication › Knowledge Management and Sharing
- Physical Sciences › Computer Science › Information Systems › Expert finding and Q&A systems
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- online communities, identity verification, knowledge contribution, information technology design, reputation management, virtual co-presence, self-presentation, member satisfaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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