Abstract
As people participate actively in social networking and peer-production sites, there are additional, implicit relations that emerge from various user activities. Mining such latent relations, or wisdom of crowds, is in itself an important area of ongoing research, with both general as well as domain-specific custom-made techniques. In this paper, we propose a new similarity measure, which we call expert-based similarity to discover semantic relations among Wikipedia articles from the co-editorship perspective. Also, different kinds of relations among entities may reveal diverse information. Both to explore and expose such a premise, we carry out a case study leveraging on multiple relations among Wikipedia articles. Specifically, we use expert-based similarity as well as other standard similarity measures, to discern the influence and impact of several factors which are hypothysed to generate controversies in Wikipedia articles. In the context of Wikipedia-specific research, our case study helps better differentiate the degree of impact of some of the possible causes of controversies.
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Notes
Note for clarification: From our analysis, we noticed that same contributor may actually contribute to many articles spread across different unrelated categories (and in that sense, the focus is not limited), e.g., on articles related to American football, Scientology and Biology, but within each specific category, the contributions are few and rather focused. The rest of the discussion is pertaining to contributions within one such category, namely “Religious Objects”, with which we carry out our case-study.
The bots in Wikipedia are automated or semi-automated tools designed by contributors to carry out some edits, for example, adding some content and some links, reverting vandalism or removing some images, to a specific class of articles. Bots must be harmless and useful and be approved by Wikipedia.
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The work is funded by A-STAR Grant No: 072 134 0055.
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Li, C., Datta, A. & Sun, A. Mining latent relations in peer-production environments: a case study with Wikipedia article similarity and controversy. Soc. Netw. Anal. Min. 2, 265–278 (2012). https://doi.org/10.1007/s13278-011-0037-5
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DOI: https://doi.org/10.1007/s13278-011-0037-5