This past August 20, I wrote blog post introducing the Wikipedia Trust Coloring Tool from the UC Santa Cruz’s Wiki Lab. Since then, the tool has been featured on slashdot and Wired. To this blogpost on slashdot, people have responded with their thoughts about the tool. Someone suggested to create a wikipedia entry about the algorithm and run the tool on the entry to assess its trustworthiness. Another person discussed the potential that those who reveal misdeeds are judged less trustworthy because their entries are likely to be edited out. In this Wired article, Bergstein acknowledges that the tool is not foolproof for the reasons just mentioned, but reveals “interesting insights”. Bergstein reports that the tool’s developer, Luca de Alfaro, hopes to work with the Wikimedia Foundation to make the tool a real-time option for users. However, no official decisions have been made. How people react to such tool and appropriate it might determine the tool’s future trajectory.

On August 31, 2007, Google News announced a feature that will remove duplicate results from its aggregated links to articles published on news outlets’ websites. This is the outcome of a licensing agreement with the Agence France Press (AFP), the Associated Press (AP), the U.K. Press Association, and the Canadian Press. On the one hand, such agreements relieve Google from lawsuits against copyright infringement on the wire services; on the other hand, Google is able to provide more original content to users and more direct access and awareness of source origin. Becoming removed from or having difficulty tracing the origin of a source is a concern that current social media models of production raise. I wonder how Google News’ model may lead to other creative approaches to easily tracing source origin in social media outlets.

For more information about the relationship between news wires services, online newspaper outlets, and Google News, see this InfoWorld article.

A study of information evaluation and coping styles of people living with HIV/AIDS reports that “assigning higher credibility to unfounded Internet information was predicted by lower incomes, less education, and avoidant copying styles.” You can read Kalichman, Cherry, Cain, Weinhardt, et al.. (2006)’s study abstract in this PubMed entry.