Review: Exploiting Social Networks for Internet Search October 4, 2007Posted by shahan in online social networks.
Tags: online social networks
Exploiting Social Networks for Internet Search, A. Mislove, K. P. Gummadi, and P. Druschel. HotNets 2006.
Of the three papers to read this week, this was by far the most interesting. Not only is it pertinent to my field of information retrieval, but it is the only one to derive results by conducting a real-world experiment. This article, which discusses a more social reason for the success in their social network search method, is in pleasant contrast to the previous required reading from Mislove et al., Measurement and Analysis of Online Social Networks, in which they conduct a battery of statistical analyses.
The focus of this paper is in the use of cached results from a connected group of individuals during their search for information. The authors demonstrate a 9% increase in the effectiveness of search results and attribute this to 3 reasons: disambiguation, ranking, and serendipity.
The paper encourages a deeper look into how large a “cluster” should be to exploit such advances in search effectiveness. In the paper’s experiment, the groups were relatively close and it will be a challenge to be able to discern groups on a larger scale especially since, as was described by Watts, 2 or 3 dimensionally independent categories are most effective in determining social relatedness. Unfortunately, the question of privacy is a very important issue and will most likely be the biggest stumbling block of putting this system into practice. This alone is a major challenge: to determine what level of social relatedness will allow someone to access a network tie’s previous searches. One possible solution is for a specialized group to offer their previous searches on a paying basis, thus becoming similar to a Google Answers system on a larger scale, a cognizant expert system if you will.