Recalling the week’s discussion on the cost of E-Freedom, I recently found an article entitled “The Worrying Consequences of the Wikipedia Gender Gap” about the disproportionate Wikipedia contributors that are male. In fact, only 13 percent of the Wikipedia contributors are women. There are many reasons as to why this is compelling especially when revisiting the discussion question “What are the costs and benefits of the free information movements…?” I consider this approach when trying to understand the influence of such few female contributors to Wikipedia.

I find it problematic that there are more male than female contributors on Wikipedia. Firstly, Wikipedia is a regularly cited and visited website. As such, many online users often are dependent on this information as the first source to their respective online inquires or searches. This means that if a persistent perspective is being established on Wikipedia there is a potentially one-sided view being presented to and accepted by online users. Secondly, there is evidence that the lack of female contributors is changing the type of information being presented. It was found in a study on Wikipedia biographies of famous figureheads in the political and pop cultural sphere and “node” connections between Wikipedia pages that there was more information on male figureheads.[i] This was discovered in the way that famous figureheads would normally link to other famous figureheads, and these node connections would typically link an online user to a male figurehead (as opposed to a female figurehead). In other words, it was more likely that an online user would find information on a male figurehead than a female figurehead because “out of a possible total of 75, only three are women: Queen Elizabeth II, Marilyn Monroe and Margaret Thatcher.”[ii] Overall, there is an obvious issue with Wikipedia as it relates to the dominant number of male contributors and the lacking information on women.

I wonder whether I find this skewed gender distribution so problematic because of the fact it is associated with and influencing Wikipedia. As I mentioned in the class discussion, Wikipedia provides readily accessible information and online users typically refer to this website in the beginning of a search. Usually a user will try to build off the information learned on Wikipedia, however, the proceeding research is possibly affected. Despite the fact that fields of academia, journalism and research rarely value Wikipedia as a credible source of information, American technologist David Weinberger finds that “at the end of “linking” you become a radical even if you started as a moderate.”[iii] Therefore, if mostly one perspective (in this instance, that of men) is contributing to Wikipedia than the opinion on the website is even more skewed due to the lack of diversity in contributors. Fortunately, as stated in the article, Wikipedia hopes to increase the contribution of women to 25 percent by 2015. However, as online users doing research, we should continuously keep in mind the perspective being presented on the “clicked on” Wikipedia page.

Original Post Date April 21, 2012

Martin Wattenberg, who also helped spearhead the Many Eyes project that we looked at briefly in class on Wednesday, created a visualization to track the edit history of articles on Wikipedia. Scraping the revision history available on all Wikipedia articles, Wattenberg and his fellow researchers Viegas and Dave used a new visualization which they dubbed a history flow, to show the relationship between the multiple iterations of a Wikipedia article over time.

The history flow visualization enabled researchers to gain insights into Wikipedia’s unique model of collaborative knowledge gathering at a glance through exploring the aesthetic and visual changes in their visualization over time. Since we only briefly touched on the topic of visualizations under the umbrella of digital art, I want to take this opportunity to advocate how digital technologies have changed our abilities to visualize data and as a consequence, understand and use it.

Pictured above is an example of the raw data format of the Wikipedia revision history. It’s obvious that it would be a time-consuming and taxing experience to parse this data “by hand” in order to achieve the same analysis tasks that Wattenberg et. al did in their history flow visualization.

Jen brings up the fascinating and important question of the gender gap in the authorship of Wikipedia articles. While Wattenberg et. al’s visualization does not address gender in particular, it does explore the social dynamics of Wikipedia creation. We have established many times in class how much data is created every day by our movements on the web. Visualization can be an invaluable tool for parsing through not only static data sets, but the dynamic social footprint we generate every day. While visualizing the connections in your Facebook network may individually simply feel like a exercise of curiosity rather than analysis, as a sociology concentrator, visualizations of social data may enable social scientists to reach a next step in research. It excites me to think how the seminal sociological work Brokerage and Closure may have been different if author Burt had at his disposal these data sets and the visual tools for exploring them.