The State of Social Computing Research: A Literature Review and Synthesis using the Latent Semantic Analysis Approach

Yibai Li · Kshiti D. Joshi

26 citations0/0 files storedJournal of the Association for Information Systems

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Knowledge Management and Sharing Computational and Text Analysis Methods Information Retrieval and Data Mining

Abstract

Social computing is an emerging research discipline. The number of publications on social computing has increased by 120% annually in the past four years. Despite the proliferation of studies in this area there is a lack of comprehensive, unified, and systematic characterization of this phenomenon. The definition and characterization of this phenomenon in the extant literature is diverse and fragmented. In this paper we attempt to bring some clarity by synthesizing and summarizing the extant literature in this area. We use Latent Semantic Analysis (LSA), a text mining and natural language processing technique, to summarize the state of social computing research. The results show that there are 27 unique dimensions which currently characterize this concept. LSA also reveals that, the 266 articles found in the literature predominantly focus on three major research themes namely, Knowledge Discovery, Knowledge Sharing, and Content Management in the Social Computing context.

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References

2005Discovering evolutionary theme patterns from text 2008Uncovering the intellectual core of the information systems discipline 2007Social Computing: An Overview 2007Research Issues in Social computing 2007Seeding the survey and analysis of research literature with text mining 1947The fund theory of accounting and its implications for financial reports 2011Causal Latent Semantic Analysis (cLSA): An Illustration

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