Almost a year ago, I was hired by Ushahidi to work as an ethnographic researcher on a project to understand how Wikipedians managed sources during breaking news events. Ushahidi cares a great deal about this kind of work because of a new project called SwiftRiver that seeks to collect and enable the collaborative curation of streams of data from the real time web about a particular issue or event. If another Haiti earthquake happened, for example, would there be a way for us to filter out the irrelevant, the misinformation and build a stream of relevant, meaningful and accurate content about what was happening for those who needed it? And on Wikipedia’s side, could the same tools be used to help editors curate a stream of relevant sources as a team rather than individuals?
When we first started thinking about the problem of filtering the web, we naturally thought of a ranking system which would rank sources according to their reliability or veracity. The algorithm would consider a variety of variables involved in determining accuracy as well as whether sources have been chosen, voted up or down by users in the past, and eventually be able to suggest sources according to the subject at hand. My job would be to determine what those variables are i.e. what were editors looking at when deciding whether to use a source or not? Continue reading “Beyond reliability: An ethnographic study of Wikipedia sources”