Journal article
Social Representations of Social Media Use in Government: An Analysis of Chinese Government Microblogging From Citizens’ Perspective
Social science computer review, Vol.34(4), pp.416-436
08/2016
DOI: 10.1177/0894439315595222
Abstract
Social media use in government has gained a rapid growth in the last few years around the world. China has witnessed a boom in social media use in government, especially government microblogging. In this study, we employ social representation theory as the primary theoretical lens to investigate Chinese government microblogging. We hope the employment of social representation theory could help us overcome the limitation that previous studies focused on the technology and government side. Interviewing data are drawn from a number of Chinese citizens for eliciting their understandings of Chinese government microblogging, followed by structural analytical procedure on the collected data. The social representation elements are obtained and presented in a map. The findings indicate that (1) social media use in government in China is at the stage of fast growth but at low interaction level; (2) governance and social media user experiences are two new but significant concepts that might have been missed in literature; (3) government microblogging does improve citizens’ perceptions toward government; however, the final outcomes like trust and accountability cannot be achieved by relying on social media use in government alone. Theoretical contributions and practitioner implications are then discussed, followed by the limitations. Finally, we present the concluding remarks for this study.
Details
- Title: Subtitle
- Social Representations of Social Media Use in Government: An Analysis of Chinese Government Microblogging From Citizens’ Perspective
- Creators
- Baozhou Lu - China University of Petroleum, Qingdao, ChinaSong Zhang - Qingdao University, Qingdao, ChinaWeiguo Fan - Pamplin College of Business, Virginia Polytechnic Institute and State University, Blacksburg, VA, USA
- Resource Type
- Journal article
- Publication Details
- Social science computer review, Vol.34(4), pp.416-436
- DOI
- 10.1177/0894439315595222
- ISSN
- 0894-4393
- eISSN
- 1552-8286
- Language
- English
- Date published
- 08/2016
- Academic Unit
- Business Analytics
- Record Identifier
- 9984083844502771
Metrics
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