Scientists Use AuthorRank-Like Logic to Assess Article Quality on Wikipedia

The results suggest that it is useful to take into account the contributor authoritativeness when assessing the information quality of Wikipedia content.

Xiangju Qin and Pádraig Cunningham from UCD have just published an interesting paper which discusses the challenges in quality assessment of Wikipedia articles. Their approach to quality scoring is based on three main modes:

  1. Edit contribution
  2. Contributor authoritativeness measures
  3. Combination of the two

The hypothesis is that Wikipedia pages with a significant number of contributions from authoritative editors are likely to be of a high quality. Cunningham and Qin measure user authority by using centrality metrics in Wikipedia talk and co-author networks:

  1. Degree
  2. Betweenness
  3. Eigenvector centrality
Here is the (percentile distribution) visualisation of Wikipedia quality scores by calculating authoritativeness in different ways:





The idea is great but personally I find little benefit in different modes of authority calculation. It seems as if basic PageRank treatment will do the job. The main issue I see is in the basic sources used to calculate authority. Given that we’re limited to Wikipedia only here, I don’t see how this could be improved, other than including temporal and revision-based metrics (which are in the proposed future work anyway).

What is interesting is that this calculation has great potential on the web in general and could help organise search results in such way that articles with high AuthorRank return higher than low AuthorRank (or no AuthorRank) articles.

The only way I see this actually working is through Google’s authorship and standardised identity networks (currently between Facebook and Google+). In the ideal world Google would use both, but if we’re realistic, it’s going to be Google+ and nothing else.

Acknowledgements: I would like to thank Jason Mun for sharing the Mashable article which helped me find the original research.

Assessing the Quality of Wikipedia Pages Using Edit Longevity and Contributor Centrality
Xiangju Qin, Pádraig Cunningham, School of Computer Science & Informatics, University College Dublin

Dan Petrovic is a well-known Australian SEO and a managing director of Dejan SEO. He has published numerous research articles in the field of search engine optimisation and online marketing. Dan's work is highly regarded by the world-wide SEO community and featured on some of the most reputable websites in the industry.

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3 Responses to “Scientists Use AuthorRank-Like Logic to Assess Article Quality on Wikipedia”

  1. Very interesting and meaningful reasch

    • Su Zhang
  2. Very much technical dan sir.. i am not getting about that chart please share info-graphic.

    • Ghanshyam Brahmbhatt
  3. Hi Dan, that’s an interesting read. I concur that with only Wikipedia in mind there’s hardly a better way to determine authority. When it comes to authority, Google+ is definitely the strongest (and perhaps the only) signal Google is going to take into account.

    • Olga

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