A Wikipedia literature review

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A Wikipedia Literature Review
Authors: Owen S. Martin [edit item]
Citation: arXiv  : . 2010 May 12.
Publication type: Working paper
Peer-reviewed: No
Database(s): arXiv (arXiv/1110.5863)
DOI: Define doi.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: No but verified
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A Wikipedia Literature Review is a publication by Owen S. Martin.


[edit] Abstract

This paper was originally designed as a literature review for a doctoral dissertation focusing on Wikipedia. This exposition gives the structure of Wikipedia and the latest trends in Wikipedia research.

[edit] Research questions

"This literature review will come in several discrete steps. First, the nature of Wikipedia must be described and catalogued, so that mathematical rigor and statistical integrity can be applied to it. Second, the history of the existing statistical technologies will be presented, for reference to the changes we apply for this problem."

Research details

Topics: Literature review [edit item]
Domains: Mathematics [edit item]
Theory type: Analysis [edit item]
Wikipedia coverage: Main topic [edit item]
Theories: "Statistical analyses" [edit item]
Research design: Literature review [edit item]
Data source: Scholarly articles [edit item]
Collected data time dimension: N/A [edit item]
Unit of analysis: Scholarly article [edit item]
Wikipedia data extraction: N/A [edit item]
Wikipedia page type: N/A [edit item]
Wikipedia language: All languages [edit item]

[edit] Conclusion

"There was literally no conclusion given in this working paper."

[edit] Comments

"Initially written for a dissertation, but the eventual dissertation mentions Wikipedia in passing only once: http://gradworks.umi.com/3490816.pdf"

[edit] References

Adler, B. and de Alfaro, L. (2007), “A Content-Driven Reputation System for the Wikipedia,” in WWW 2007, Proceedings of the 16th International World Wide Web Conference.

Auer, S. and Lehmann, J. (2007), “What have innsbruck and leipzig in common? extracting semantics from wiki content,” The Semantic Web: Research and Applications, 503–517.

Barabasi, A. (2003), Linked: How everything is connected to everything else and what it means, Penguin Group New York.

Berners-Lee, T., Hendler, J., and Lassila, O. (2001), “The Semantic Web,” Scientific American, 284, 34–43.

Beschastnikh, I., Kriplean, T., and McDonald, D. (2008), “Wikipedian self-governance in action: Motivating the policy lens,” in Proceedings of International Conference on Webblogging and Social Media (ICWSM’08).

Blumenstock, J. E. (2008), “Size matters: Word count as a measure of quality on wikipedia,” in Proceedings of the 17th international conference on World Wide Web (WWW) 2008, pp. 1095–1096.

Christensen, C. (1997), The innovator’s dilemma: when new technologies cause great firms to fail, Harvard Business Press.

Dondio, P. and Barrett, S. (2007), “Computational trust in web content quality: A comparative evalutation on the wikipedia project,” Informatica, 31, 151–160.

Erd ̈s, P. and R ́nyi, A. (1959), “On random graphs,” Publ. Math. Debrecen, 6, 156.

Fallis, D. (2008), “Toward an epistemology of Wikipedia,” Journal of the American Society for Information Science and Technology, 59, 1662–1674.

Galilei, G. (1632), “Dialogue concerning the two chief world systems: The Ptolemaic and the Copernican,” Gio Pertista Landini.

Hoffmann, R., Amershi, S., Patel, K., Wu, F., Fogarty, J., and Weld, D. (2009), “Amplifying community content creation with mixed initiative information extraction,” in Proceedings of the 27th international conference on Human factors in computing systems, ACM, pp. 1849–1858.

Hu, M., Lim, E.-P., Sun, A., Lauw, H. W., and Vuong, B.-Q. (2007), “Measuring article quality in wikipedia: Models and evaluation,” in CIKM’07.

Knights, D., Mozer, M., and Nicolov, N. (2009), “Detecting Topic Drift with Compound Topic Models,” Proceedings of the Third International ICWSM Conference.

Kriplean, T., Beschastnikh, I., and McDonald, D. W. (2008), “Articulations of wiki-work: Uncovering valued work in wikipedia through barnstars,” in CSCW ’08: Proceedings of the ACM 2008 conference on Computer supported cooperative work, New York, NY, USA: ACM, pp. 47–56.

Lerman, K. and Hogg, T. (2009), “Stochastic Models of Large-Scale Human Behavior on the Web,” .

Manning, C., Raghavan, P., and Schtze, H. (2008), Introduction to Information Retrieval., Cambridge University Press, Cambridge, UK.

Manning, C. and Schutze, H. (2002), Foundations of statistical natural language processing, MIT Press.

Olleros, F. (2008), “Learning to Trust the Crowd: Some Lessons from Wikipedia,” in Proceedings of the 2008 International MCETECH Conference on e-Technologies, IEEE Computer Society, pp. 212–216.

Ortega, F., Gonzalez-Barahona, J., and Robles, G. (2008), “On the inequality of contributions to Wikipedia,” in 41st Annual Hawaii International Conference on System Sciences (HICSS’08), pp. 304–311.

Pareto, V. (1901), “The rise and fall of elites: an application of theoretical sociology,” Rivista italiana di sociologia.

Potthast, M., Stein, B., and Gerling, R. (2008), “Automatic vandalism detection in Wikipedia,” Advances in Information Retrieval, 663–668.

Segaran, T., Evans, C., and Taylor, J. (2009), Programming the semantic web, O’Reilly Media.

Thomas, C. and Sheth, A. (2007), “Semantic convergence of wikipedia articles,” in Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, IEEE Computer Society, pp. 600–606.

Thomas Wohner and Ralf Peters (2009), “Assessing the quality of wikipedia articles with lifecycle based metrics,” in The Proceedings of the 5th International Symposium on Wikis and Open Collaboration.

Viegas, F., Wattenberg, M., and McKeon, M. (2007), Online Communities and Social Computing, Springer, chap. The Hidden Order Of Wikipedia, pp. 445–454.

Voss, J. (2005), “Measuring Wikipedia,” in International Conference of the International Society for Scientometrics and Informetrics: 10th, Stockholm.

Warren, R., Airoldi, E., and Banks, D. (2008), “Network Analysis of Wikipedia,” Statistical Methods in E-Commerce Research, 81.

Wu, F. and Weld, D. (2007), “Autonomously semantifying wikipedia,” in Proceedings of the sixteenth ACM conference on Conference on information and knowledge management, ACM, pp. 41–50.

— (2008), “Automatically refining the Wikipedia infobox ontology,” in WWW 2008, ACM New York, NY, USA.

Zeng, H., Alhossaini, M. A., Ding, L., Fikes, R., and McGuinness, D. L. (2006), “Computing trust from revision history,” in Proceedings of the 2006 International onference on Privacy, Security and Trust: Bridge the Gap Between PST Technologies and Business Services.

Zipf, G. K. (1949), Human Behavior and the Principle of Least Effort, Addison-Wesley Press.

Further notes[edit]

Facts about "A Wikipedia literature review"RDF feed
AbstractThis paper was originally designed as a literature review for a doctoral dissertation focusing on Wikipedia. This exposition gives the structure of Wikipedia and the latest trends in Wikipedia research.
Added by wikilit teamNo but verified +
Collected data time dimensionN/A +
CommentsInitially written for a dissertation, but the eventual dissertation mentions Wikipedia in passing only once: http://gradworks.umi.com/3490816.pdf
ConclusionThere was literally no conclusion given in this working paper.
Data sourceScholarly articles +
Dates12 +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22A%2BWikipedia%2BLiterature%2BReview%22 +
Has authorOwen S. Martin +
Has domainMathematics +
Has topicLiterature review +
MonthMay +
Peer reviewedNo +
Publication typeWorking paper +
Published inArXiv +
Research designLiterature review +
Research questionsThis literature review will come in severaThis literature review will come in several discrete steps. First, the nature of

Wikipedia must be described and catalogued, so that mathematical rigor and statistical integrity can be applied to it. Second, the history of the existing statistical

technologies will be presented, for reference to the changes we apply for this problem.
to the changes we apply for this problem.
Revid11,224 +
TheoriesStatistical analyses
Theory typeAnalysis +
TitleA Wikipedia Literature Review
Unit of analysisScholarly article +
Urlhttp://arxiv.org/abs/1110.5863 +
Wikipedia coverageMain topic +
Wikipedia data extractionN/A +
Wikipedia languageAll languages +
Wikipedia page typeN/A +
Year2010 +