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Keeping up on Current Events! A Case Study of Newcomers to Wikipedia

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Book cover Social Informatics (SocInfo 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11185))

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Abstract

Online production communities such as Wikipedia and OpenStreetMap play an important role in connecting the public with major events in society. The popularity of a major event, together with the popularity of online communities brings the general public to collaborate on and co-create knowledge about the event. The high level of interest in capturing what draws the attention of society can particularly help online production communities meet one of the essential challenges they face: attracting and retaining newcomers. In this work, we explore how newcomers in such communities respond to knowledge production around major societal events. Analysis of the participation of 506 newcomers to Wikipedia articles related to three highly popular events shows that the popularity of the events attracts a new wave of users to the online community. These newcomers provide valuable contributions to the community, however, at a differing level depending on their initial motivation and experiences. Those participants who joined the online community solely to contribute to one topic or event are more likely to face challenges in contribution and leave Wikipedia after limited contribution. We discuss factors and patterns of newcomers’ early and longer-term participation in Wikipedia in relation to three popular events.

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Notes

  1. 1.

    https://www.mediawiki.org/wiki/API:Main_page.

  2. 2.

    https://en.wikipedia.org/wiki/Portal:Current_events.

  3. 3.

    https://en.wikipedia.org/wiki/Help:Category.

  4. 4.

    https://en.wikipedia.org/wiki/Category:Black_Lives_Matter.

  5. 5.

    https://en.wikipedia.org/wiki/Category:2014_FIFA_World_Cup.

  6. 6.

    https://en.wikipedia.org/wiki/Category:West_African_Ebola_virus_epidemic.

  7. 7.

    We excluded any editors who had been blocked from Wikipedia.

  8. 8.

    https://trends.google.com/trends/.

  9. 9.

    https://www.mediawiki.org/wiki/ORES.

  10. 10.

    https://ores.wikimedia.org/.

  11. 11.

    Due to computing limitation, we only collected the good-faith quality and reverts within four months after registration. As newcomers’ editing quality has already converged at a relatively stable level within even first couple weeks, the four months data is a reasonable time period to evaluate the contribution quality.

  12. 12.

    http://pythonhosted.org/mwreverts/.

  13. 13.

    http://www.who.int/mediacentre/news/statements/2014/ebola-20140808/en/.

  14. 14.

    Represented graphs are included in Appendix Fig.  5. Figure 6 visualized the editors’ registration activities which are also corresponding to the major current events.

  15. 15.

    Hazard Ratio can be interpreted as: one degree increase in out-degree reduces the hazard by a factor of 0.0001, or 99.99%.

  16. 16.

    Another example can be found at https://en.wikipedia.org/w/index.php?title=Charlestonchurchshooting&type=revision&diff=667541754.

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Correspondence to Rosta Farzan .

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Fig. 5.
figure 5

Newcomer editing activity timeline correspond closely with the Google trend as well as the offline current event timeline

Fig. 6.
figure 6

Newcomer registration timeline correspond closely with the Google trend as well as the offline current event timeline: This figure visualizes the monthly registration activity of the event-driven newcomers. As presented in the graph, we observed that peaks in the event-driven newcomers’ registration activity closely corresponds to the offline events for all three cases.

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Li, A., Farzan, R. (2018). Keeping up on Current Events! A Case Study of Newcomers to Wikipedia. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11185. Springer, Cham. https://doi.org/10.1007/978-3-030-01129-1_22

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