TY - JOUR
T1 - Visualizing large-scale human collaboration in Wikipedia
AU - Biuk-Aghai, Robert P.
AU - Pang, Cheong Iao
AU - Si, Yain Whar
PY - 2014/2
Y1 - 2014/2
N2 - Volunteer-driven large-scale human-to-human collaboration has become common in the Web 2.0 era. Wikipedia is one of the foremost examples of such large-scale collaboration, involving millions of authors writing millions of articles on a wide range of subjects. The collaboration on some popular articles numbers hundreds or even thousands of co-authors. We have analyzed the co-authoring across entire Wikipedias in different languages and have found it to follow a geometric distribution in all the language editions we studied. In order to better understand the distribution of co-author counts across different topics, we have aggregated content by category and visualized it in a form resembling a geographic map. The visualizations produced show that there are significant differences of co-author counts across different topics in all the Wikipedia language editions we visualized. In this article we describe our analysis and visualization method and present the results of applying our method to the English, German, Chinese, Swedish and Danish Wikipedias. We have evaluated our visualization against textual data and found it to be superior in usability, accuracy, speed and user preference.
AB - Volunteer-driven large-scale human-to-human collaboration has become common in the Web 2.0 era. Wikipedia is one of the foremost examples of such large-scale collaboration, involving millions of authors writing millions of articles on a wide range of subjects. The collaboration on some popular articles numbers hundreds or even thousands of co-authors. We have analyzed the co-authoring across entire Wikipedias in different languages and have found it to follow a geometric distribution in all the language editions we studied. In order to better understand the distribution of co-author counts across different topics, we have aggregated content by category and visualized it in a form resembling a geographic map. The visualizations produced show that there are significant differences of co-author counts across different topics in all the Wikipedia language editions we visualized. In this article we describe our analysis and visualization method and present the results of applying our method to the English, German, Chinese, Swedish and Danish Wikipedias. We have evaluated our visualization against textual data and found it to be superior in usability, accuracy, speed and user preference.
KW - Category
KW - Co-authoring
KW - Information visualization
KW - Visualization of collaborative processes & applications
KW - Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=84890120140&partnerID=8YFLogxK
U2 - 10.1016/j.future.2013.04.001
DO - 10.1016/j.future.2013.04.001
M3 - Article
AN - SCOPUS:84890120140
SN - 0167-739X
VL - 31
SP - 120
EP - 133
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
IS - 1
ER -