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Research:Newsletter/2014/December

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Wikimedia Research Newsletter

Vol: 4 • Issue: 12 • December 2014 [contribute] [archives]

Wikipedia in higher education; gender-driven talk page conflicts; disease forecasting


With contributions by: Federico Leva, Piotr Konieczny, Maximilian Klein, Tilman Bayer and Pine

Use of Wikipedia in higher education influenced by peer opinions and perception of Wikipedia's quality

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The Universitat Oberta de Catalunya (Open University of Catalonia) in Barcelona, Spain

A paper titled "Factors that influence the teaching use of Wikipedia in Higher Education"[1] uses the technology acceptance model to shed light on faculty's (of Universitat Oberta de Catalunya) views of Wikipedia as a teaching tool. The main factors are shown to be the perception of colleagues’ opinion about Wikipedia and the perceived quality of the information on Wikipedia. As the authors note, while prior studies also pointed to the quality concerns, this study suggests a causal link between colleagues' views and one's perception of Wikipedia quality. The authors conclude that the strong peer culture within academia makes the importance of role models very significant, which in turn has implications for the segment of the Wikimedia movement that desires greater ties with the academic world. The authors also note that "despite the lack of institutional support and acknowledgement, a growing number of academics think it is very useful and desirable to publish research results or even intermediate data in open repositories", an attitude that also correlates positively with positive views of Wikipedia. To quote the authors' very valid recommendation: "For those faculty members already using Wikipedia as a learning tool, we think it would have greater impact if they publicly acknowledged their practices more, especially to their close colleagues, and explain their own teaching experiences as well as the effects it has had on the students’ academic performance." The team behind the paper is also partnering in the Wikidata for research project featured in News and notes.

Analysis of two gender-driven talk page conflicts on the German-language Wikipedia

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Reviewed by Maximilianklein (talk)

"Gender differences within the German-language Wikipedia"[2] is a pair of close readings of two gender-driven talk page conflicts on the German Wikipedia from 2006 and 2013, "show[ing] exemplarily that a) the feministic gender discourse in Wikipedia is not appreciated – primarily by male Wikipedians – [...] and b) that discussions behind the scenes of Wikipedia can feature an unpleasant and rude nature, that is not very appealing and motivating for female contributors". The analysis aims to focus on the communication styles of the gendered personalities as viewed under the critical rubrics of Margarete Jäger and Nina Schuppener. In the degenerating arguments around whether or not the welcome message on the German Wikipedia's main page (2006 thread) and German Wikipedia articles in general (2013/14 straw poll talk page) should use generic male pronouns and nouns, or newer more neutral alternatives, like using parentheses in "Mitarbeiter(in)", it is highlighted that the male-appearing participants use instruction and discrediting statements; and the female-appearing tend to question intellectual capabilities and give advice. Finally the authors conclude that "the most crucial point is the fact that the female author gave up [first]," stopping responding less than 24 hours into the discussion, and that the change advocated for was not enacted. These deconstructed examples add to an evidence of a hypothesis that minority voices are crowded out in Open Culture, as purported by the "Free as in Sexist" theory.

Briefly

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"Original map by John Snow showing the clusters of cholera cases in the London epidemic of 1854" as seen in the English Wikipedia article Epidemiology.

History of the Spanish Wikipedia's ArbCom

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A short recounting by Sefidari and Ortega (pre-print) summarised the history of the Spanish Wikipedia Comité de resolucíon de conflictos (arbitration committee), which existed from 2007 to 2008. It was composed of admins, received complaints which in 80 % of cases involved admins, dismissed nearly all cases presented, ruled against the claimant in a large majority of accepted cases, and was finally dissolved in 2009.[3]

Two new papers on disease forecasting using Wikipedia

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Yet another study (pre-print), considering 5 articles, showed that English Wikipedia page views trends can forecast the peak in influenza-like illnesses in the USA. Essentially, by visiting the articles in question, users are self-reporting their (suspect) disease, some weeks in advance of the data collected centrally by a government agency based on medical practitioners' reports of the same.[4] Another study, again focused on some English Wikipedia articles, reached the same conclusion with slightly different (and, notably, fully open source) methods, for 14 diseases, while producing a useful list of some dozens past studies on the matter.[5]

Wikipedia as a source of health information during salmonella outbreak

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A statistically significant survey in the Netherlands assessed with what efficacy the population was informed about Salmonella infection during an outbreak in the country. Nearly all information was received passively (mainly from TV, radio and newspapers, but also social media); of the minuscule minority who actively sought information, most turned to their newspaper website, or ended up (with highest satisfaction among all sources) on official websites or Wikipedia.[6]

Most MoodBar users became longer-term contributors

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A study on one dataset produced by the (mostly discontinued) MoodBar tool showed that the newcomers who gave feedback via the MoodBar were significantly more likely to become longer-term contributors. After six months, 3.6% of editors who were able to use the MoodBar were still editing, compared to 3.3% of those who did not have the option.[7]

New R libraries for Wikipedia research

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A new R programming language library "wikipediatrend"[8] that facilitates longitudinal page-view analyses has been created. The package is a wrapper on top of long-time service stats.grok.se|Wikipedia:Stats.grok.se|stats.grok.se. This marks an uptick in the popularity of the R language for Wikipedia analysis as WikipediR was also recently released which itself wraps many common mediawiki API calls.

Use of Wikinews to teach journalism students

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This paper[9] discusses an educational project that used Wikinews in an undergraduate journalism course at the Australian University of Wollongong. While the use of Wikipedia in education has dominated the relevant discussions, Wikinews seems like a valuable, yet underused tool for journalists-in-training. Though this essay-like paper seems to describe the experience in a positive fashion, it does not contain any specific conclusions, nor a list of articles edited by the students that would allow for a more-in depth commentary in the context of the Wikimedia learning experience.

"Linking Today's Wikipedia and News from the Past"

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This workshop paper[10] presents a method to automatically identify articles in the New York Times archive matching a particular event mentioned on Wikipedia (dataset).


Other recent publications

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A list of other recent publications that could not be covered in time for this issue – contributions are always welcome for reviewing or summarizing newly published research.

  • "An Empirical Study of Motivations for Content Contribution and Community Participation in Wikipedia"[11] From the abstract: "The research findings show that content contribution is more driven by extrinsically oriented motivations, including reciprocity and the need for self-development, while community participation is more driven by intrinsically oriented motivations, including altruism and a sense of belonging to the community."
  • "Wikipedia as a Time Machine"[12] (presented at WWW 2014)
  • "Hacking Trademark Law for Collaborative Communities"[13] (related website: http://collabmark.org/ )
  • "The political economy of wilkiality: a South African inquiry into knowledge and power on wikipedia"[14] (PhD Thesis)
  • "Predicting Low-Quality Wikipedia Articles Using User's Judgements"[15] From the abstract: "In this paper, we utilize article ratings from Wikipedia users for the first time to assess article quality. We define 'low-quality' based on those ratings and design automatic methods to identify potential low-quality articles."
  • "Infoboxer: Using Statistical and Semantic Knowledge to Help Create Wikipedia Infoboxes"[16]
  • "On the Use of Reliable-Negatives Selection. Strategies in the PU Learning Approach for Quality Flaws Prediction in Wikipedia."[17]


References

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  1. ↑ Meseguer Artola, Antoni; Eduard Aibar Puentes; Josep Lladós Masllorens; Julià Minguillón Alfonso; Maura Lerga Felip (2014-12-11). "Factors that influence the teaching use of Wikipedia in Higher Education" (Article). 
  2. ↑ Sichler, Almut; Elizabeth Prommer (2014-12-22). "Gender differences within the German-language Wikipedia". ESSACHESS - Journal for Communication Studies 7 (2(14)): 77–93. ISSN 1775-352X. 
  3. ↑ Sefidari, Maria; Felipe Ortega (2014-12-10). "Evaluating arbitration and conflict resolution mechanisms in the Spanish Wikipedia". arXiv:1412.3695 [cs]. 
  4. ↑ Hickmann, Kyle S.; Geoffrey Fairchild; Reid Priedhorsky; Nicholas Generous; James M. Hyman; Alina Deshpande; Sara Y. Del Valle (2014-10-22). "Forecasting the 2013--2014 Influenza Season using Wikipedia". arXiv:1410.7716 [q-bio, stat]. 
  5. ↑ Generous, Nicholas; Geoffrey Fairchild; Alina Deshpande; Sara Y. Del Valle; Reid Priedhorsky (2014-11-13). "Global Disease Monitoring and Forecasting with Wikipedia". PLoS Comput Biol 10 (11). doi:10.1371/journal.pcbi.1003892. 
  6. ↑ Velsen, Lex van; DesiréJMA Beaujean; Julia EWC van Gemert-Pijnen; Jim E. van Steenbergen; Aura Timen (2014-01-31). "Public knowledge and preventive behavior during a large-scale Salmonella outbreak: results from an online survey in the Netherlands". BMC Public Health 14 (1): 100. ISSN 1471-2458. PMID 24479614. doi:10.1186/1471-2458-14-100. 
  7. ↑ Ciampaglia, Giovanni Luca; Dario Taraborelli (2014-09-04). "MoodBar: Increasing new user retention in Wikipedia through lightweight socialization". arXiv:1409.1496 [physics]. 
  8. ↑ Meissner, Peter. "Introduction to Public Attention Analytics with Wikipediatrend". Retrieved 31 December 2014. 
  9. ↑ Blackall, David (2014). "Learning skills in journalistic skepticism while recognising whistleblowers" (PDF). The European Conference on Education 2014 Brighton, United Kingdom Official Conference Proceedings. Naka Ward, Nagoya, Aichi Japan: The International Academic Forum (IAFOR). ISSN 2188-1162. 
  10. ↑ Mishra, Arunav (2014). Linking Today's Wikipedia and News from the Past. Proceedings of the 7th Workshop on Ph.D Students. PIKM '14. New York, NY, USA: ACM. pp. 1–8. ISBN 978-1-4503-1481-7. doi:10.1145/2663714.2668048.    / preprint PDF
  11. ↑ Xu, Bo; Dahui Li. "An Empirical Study of Motivations for Content Contribution and Community Participation in Wikipedia". Information & Management. ISSN 0378-7206. doi:10.1016/j.im.2014.12.003.   
  12. ↑ Stewart Whiting, Joemon M. Jose, Omar Alonso: Wikipedia as a Time Machine. WWW’14 Companion, April 7–11, 2014, Seoul, Korea. PD
  13. ↑ Welinder, Yana; Stephen LaPorte (2014-08-05). Hacking Trademark Law for Collaborative Communities. Rochester, NY: Social Science Research Network. 
  14. ↑ Ovesen, Håvard (2014). "The political economy of wilkiality: a South African inquiry into knowledge and power on wikipedia". 
  15. ↑ Zhang, Ning; Lingyun Ruan; Luo Si (2015-01-01). "Predicting Low-Quality Wikipedia Articles Using User's Judgements". In Elisa Bertino, Sorin Adam Matei (eds.). Roles, Trust, and Reputation in Social Media Knowledge Markets. Computational Social Sciences. Springer International Publishing. pp. 91–99. ISBN 978-3-319-05467-4.   
  16. ↑ Roberto Yus, Varish Mulwad, Tim Finin, and Eduardo Mena: "Infoboxer: Using Statistical and Semantic Knowledge to Help Create Wikipedia Infoboxes" PDF
  17. ↑ Edgardo Ferretti, Marcelo Errecalde, Maik Anderka, Benno Stein: On the Use of Reliable-Negatives Selection. Strategies in the PU Learning Approach for Quality Flaws Prediction in Wikipedia. In: Proceedings of the 25th International Workshop on Database and Expert Systems Applications (DEXA’14): 11th International Workshop on Text-based Information Retrieval (TIR’14), Munich, Germany, 2014. IEEE. PDF


Wikimedia Research Newsletter
Vol: 4 • Issue: 12 • December 2014
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