| James Purtilo|
(Alternative names for this author)
|Co-authors||Jeff C. Stuckman, Jeffrey Stuckman|
|Authorship||Publications (2), datasets (0), tools (0)|
|Citations||Total (0), average (0), median (0), max (0), min (0)|
|DBLP · Google Scholar|
|Export and share|
|BibTeX, CSV, RDF, JSON|
|Browse properties · List of authors|
James Purtilo is an author.
PublicationsOnly those publications related to wikis are shown here.
|Title||Keyword(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Analyzing the wikisphere: Methodology and data to support quantitative wiki research||Journal of the American Society for Information Science and Technology||English||August 2011||Owing to the inherent difficulty in obtaining experimental data from wikis, past quantitative wiki research has largely focused on Wikipedia, limiting the ability to generalize such research. To facilitate the analysis of wikis other than Wikipedia, we developed WikiCrawler, a tool that automatically gathers research data from public wikis without supervision. We then built a corpus of 151 wikis, which we have made publicly available. Our analysis indicated that these wikis display signs of collaborative authorship, validating them as objects of study. We then performed an initial analysis of the corpus and discovered some similarities with Wikipedia, such as users contributing at unequal rates. We also analyzed distributions of edits across pages and users, resulting in data which can motivate or verify mathematical models of behavior on wikis. By providing data collection tools and a corpus of already-collected data, we have completed an important first step for investigations that analyze user behavior, establish measurement baselines for wiki evaluation, and generalize Wikipedia research by testing hypotheses across many wikis.||0||0|
|Measuring the Wikisphere||WikiSym||2009||Due to the inherent difficulty in obtaining experimental data from wikis, past quantitative wiki research has largely been focused on Wikipedia, limiting the degree that it can be generalized. We developed WikiCrawler, a tool that automatically downloads and analyzes wikis, and studied 151 popular wikis running Mediawiki (none of them Wikipedias). We found that our studied wikis displayed signs of collaborative authorship, validating them as objects of study. We also discovered that, as in Wikipedia, the relative contribution levels of users in the studied wikis were highly unequal, with a small number of users contributing a disproportionate amount of work. In addition, power-law distributions were successfully fitted to the contribution levels of most of the studied wikis, and the parameters of the fitted distributions largely predicted the high inequality that was found. Along with demonstrating our methodology of analyzing wikis from diverse sources, the discovered similarities between wikis suggest that most wikis accumulate edits through a similar underlying mechanism, which could motivate a model of user activity that is applicable to wikis in general.||9||0|