I read the paper (the summarized version that I found at http://www.mpi-sws.mpg.de/~amislove/publications/PeerSpective-HotNets.pdf) and I think the idea of improving search based on information gleaned from social relatedness is great.

There are things I don’t understand, though:
-In the paper, it is described how the HTTP proxy installed on the computers of the peers voluntarily participating in the experiment was used to index the URLs visited by these users. The queries submitted to the PeerSpective system were matched against these indexes distributed in these peers (if I am not mistaken). I don’t thus see how this is different from just a distributed (decentralized) search system. If this was done in a group consisting multiple social circles, was there any mechanism stated for discerning to what social circle an individual belonged to? In the absence of that, how is their system different from a decentralized Web search engine?
-One of the problems of conventional search engines pointed out by the authors was the lack of indexing on non-html pages. How would the use of social network-based searching do away with this problem? I didn’t see any data related to this point in the results of the experiment. Did I miss something?
-Again I don’t see how the idea of improving results on pages in the deep web or dark web… relate to social network based search than to the search merely being distributed.
-Finally, the authors raised an interesting point in noting that the ranking of a search result can be fine tuned based on an individual’s “context” of the term- the context being derived from what social network the individual belongs to. However, while I thought this would at the same time reduce the “serendipity” of the information in the query results as the information would be defined in a narrow context, the authors contended the reverse. What do you think?

I am eager to hear your comments on each one of the above.

S.T.