A study on knowledge quality and job performance of knowledge workers by analyzing content of social network sites using sentiment network analysis

Lim, Justin Renn Aun and Lee, Angela Siew Hoong * and Lim, Tong Ming * (2013) A study on knowledge quality and job performance of knowledge workers by analyzing content of social network sites using sentiment network analysis. Information Management and Business Review, 5 (11). pp. 525-530. ISSN 2220-3796 (Submitted)

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Abstract

The importance of knowledge quality has become a key research area in recent research works. Many organizations realize that benefits of knowledge creation and sharing cannot be obtained unless quality of knowledge is achieved. This research investigates the perception of knowledge workers that uses social network sites as a means for social interaction, collaboration and knowledge sharing. The entries posted by these knowledge workers on the social network sites are gathered and studied with the presence of the element of sentiment such as emotion using sentiment network analysis. Based on the analysis, the results investigate the relationship between sentiment and quality of knowledge shared among knowledge workers on social networking sites and individual job performance. This research will analyse the improvements of employees’ job performance through the quality knowledge using interview, questionnaire survey, and text analysis to look for conversational patterns and element of sentiment. This research will investigate a number of knowledge driven companies that use social network sites. Structural Equation Modelling (SEM) is used to analyse responses collected from survey data.

Item Type: Article
Additional Information: Second and third authors are with the Dept. of Information Systems, Faculty of Science and Technology, Sunway University.
Uncontrolled Keywords: Knowledge Sharing; Knowledge Quality; Job Performance; Social Network Sites; Sentiment Network Analysis
Subjects: Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Z Bibliography. Library Science. Information Resources > ZA Information resources
Divisions: Sunway University > School of Science and Technology > Dept. Information Systems
Depositing User: Ms. Molly Chuah
Date Deposited: 31 Mar 2015 07:19
Last Modified: 31 Mar 2015 08:32
URI: http://eprints.sunway.edu.my/id/eprint/251

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