Using big data and network analysis to understand Wikipedia article quality

Jun Liu, Sudha Ram

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The research reported in this paper focuses on the question of why Wikipedia articles are different in quality. Since these articles are developed in an open and social environment, our work investigates if the social capital of contributors plays a role in determining the quality of the articles. We focus on three major types of social capital with respect to teams of contributors working on Wikipedia articles: internal bonding, external bridging and functional diversity. Through a social network analysis of these articles based on a dataset extracted from its edit history, our research finds that all three types of social capital have a significant impact on their quality. In addition, we found that internal bonding interacts positively with external bridging resulting in a multiplier effect on article quality. The findings of our research have implications for developing automated techniques for quality assessment of Wikipedia and also provide insights into improving quality of these articles.

Original languageEnglish (US)
JournalData and Knowledge Engineering
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Network analysis
Wikipedia
Social capital
Quality assessment
Functional diversity
Social network analysis
Social environment
Multiplier

ASJC Scopus subject areas

  • Information Systems and Management

Cite this

Using big data and network analysis to understand Wikipedia article quality. / Liu, Jun; Ram, Sudha.

In: Data and Knowledge Engineering, 01.01.2018.

Research output: Contribution to journalArticle

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