Submissions:2014/Measuring Editor Collaborativeness With Economic Modelling

Measuring Editor Collaborativeness With Economic Modelling
 * Title of the submission:

Community - presents a way to characterise editors.
 * Themes (Proposal Themes - Community, Tech, Outreach, GLAM, Education):

Presentation
 * Type of submission (Presentation Types - Panel, Workshop, Presentation, etc):

Max Klein
 * Author of the submission:

isalix@gmail.com
 * E-mail address:

w:User:Maximilianklein
 * Username:

California
 * US state or country of origin:


 * Affiliation, if any (organization, company etc.):


 * Personal homepage or blog:

Even though Wikipedia is a vanguard of collaboration, Wikipedians unfortunately have access to few tools for performance metrics - most notably “Edit Count”. The Wikimedia Foundation's WikiMetrics cohort notion has begun the search for higher-level metrics, but hasn't yet answered “how” users work together.
 * Abstract (at least 300 words to describe your proposal):

This presentation will outline new methods for measuring and understanding editor collaborativeness. Borrowing from Economic modelling, new insights on economic competitiveness make the analog of editor collaborativeness possible. A recent stream of research in Macroeconomics has shown simple techniques for predicting GDP with very little information, which can be translated into the wiki realm. Using only the data of which countries export which products (not even how much of each product), one can quickly predict GDP rankings. Here we re-purpose the algorithm, so that Editors are countries, articles are products, and GDP is “Total Labour Hours” (an edit count derivative ).

By constructing a relation between editors and the articles they have touched, we are able to produce an entirely new perspective on Wikipedia (see the Figure below). The simplicity of this model can help us to quickly and easily determine which categories of articles are more likely to be hostile and power-user dominated, and which are more egalitarian and collaborative.

Incredibly, this borrowed method works even better for Wikis than Economies. Where the maximum achievable correlation in Macroeconomics is about 0.42, we can achieve correlations of up to 0.91. However, the real innovation comes from two factors which are tweaked to optimize the model:


 * importance of the high quality articles in an editor's contribution portfolio
 * (conversely) the importance of highly-invested editors in an article's contribution history.

These variables can range independently, and characterize our notion of "collaborativeness".

Collaborativeness is determined from the edit patterns of editors. Do they edit many articles? How well developed are the articles they edit? Consider these telling extremes:


 * The best editors in Category:Military history of the US&mdash;a category known for being very competitive&mdash;are characterized by emphasizing investment in touching many articles in the category. Less collaborative.
 * On the other end, the editors in Category:Sexual acts&mdash;a taboo subject where much editing could be considered perverse&mdash;are characterized by not touching many articles in the category. More collaborative.

We hope to receive critique on whether our algorithmic notion of collaborativeness is inline with community opinion. Additionally we hope to receive requests for different datasets to analyze for future research.

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