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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Individual Behavioral Consistency in Virtual Communities

Individual Behavioral Consistency in Virtual Communities
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Author(s): Zheng Xin (Fudan University, China), Zhang Cheng (National University of Singapore, Singapore)and Chan Hock Chuan (National University of Singapore, Singapore)
Copyright: 2003
Pages: 3
Source title: Information Technology & Organizations: Trends, Issues, Challenges & Solutions
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59140-066-0.ch188
ISBN13: 9781616921248
EISBN13: 9781466665330


Compared to a traditional community, relational contact via computermediated communication (CMC) becomes the main behavior in a virtual community (VC). Consequently individual behaviors are different from that in real life. Previous studies on VC claimed contradictory impacts on individual behavior: some believed interpersonal relation became hokey in the community while others thought it became genuine. Therefore a question on individual behavior in VC arises: as the physical world changes to the virtual one, will individuals still keep their behaviors probabilistically consistent? Using individuals in online alumni associations as samples, we study consistency of individual behavior, i.e. whether individuals behave consistently across time in a VC; and the impact of the environmental stimuli on individual behavior, i.e. whether individuals behave differently in different VCs across time. Posted messages in the forum, including the posting frequency and message length, are chosen as the objective measurement of individual behavior in this study. The result shows that individuals still keep their consistency in VC activities, as in the physical community. However it is not so clear about consistency across VCs. This behavioral study provides a fresh approach to analyze individual behavior in CMC: firstly behavioral information is mined objectively, to avoid any psychological bias from subjective data; secondly it emphasizes on discovery of common behavioral characteristics from regular life, rather than seeking their internal causes.

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