Network Analysis of User Generated Content Quality in Wikipedia
|Network Analysis of User Generated Content Quality in Wikipedia|
|Author(s)||Myshkin Ingawale, Amitava Dutta, Rahul Roy, Priya Seetharaman|
|Published in||Online Information Review|
|Keyword(s)||Wikipedia, network analysis, social computing, structural holes, user generated content, quality|
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Social media platforms allow near-unfettered creation and exchange of User Generated Content (UGC). We use Wikipedia, which consists of interconnected user generated articles. Drawing from network science, we examine whether high and low quality UGC in Wikipedia differ in their connectivity structures. Using featured articles as a proxy for high quality, we undertake a network analysis of the revision history of six different language Wikipedias to offer a network-centric explanation for the emergence of quality in UGC. The network structure of interactions between articles and contributors plays an important role in the emergence of quality. Specifically, the analysis reveals that high quality articles cluster in hubs that span structural holes. The analysis does not capture the strength of interactions between articles and contributors. The implication of this limitation is that quality is viewed as a binary variable. Extensions to this research will relate strength of interactions to different levels of quality in user generated content. Practical implications Our findings help harness the ‘wisdom of the crowds’ effectively. Organizations should nurture users and articles at the structural hubs, from an early stage. This can be done through appropriate design of collaborative knowledge systems and development of organizational policies to empower hubs. Originality The network centric perspective on quality in UGC and the use of a dynamic modeling tool are novel. The paper is of value to researchers in the area of social computing and to practitioners implementing and maintaining such platforms in organizations.
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