Long live Google! Maybe not?
BlogCatalog launched its Social Search today. The search results, from Social Search, provide a fascinating view into the online social network activities of close to 100,000 bloggers. While doing a search on Wikipedia, after the launch, I came across the entry for Social Search Engine. The entry describes a Social Search Engine, in part, as:
“… a type of search engine that determines the relevance of search results by considering the interactions or contributions of users. Example forms of user input include social bookmarking or direct interaction with the search results such as promoting or demoting results the user feels are more or less relevant to their query.”
Under this definition, Digg, Delicious and Wikipedia, while visibly different, are all social search engines. Moreover, according to Wikipedia, Google with their backlink algorithm could also be considered part of social search “because PageRank is relying on the collective judgement of webmasters linking to other content on the web. Links, in essence, are positive votes by the webmaster community for their favorite sites.”
After reading Wikipedia’s definition, it occurred to me that this traditional definition of social search engines, and social search, should be adjusted to more accurately reflect changes in online social networks and the underlying technologies. That is, the rapid growth of social networks and the opening up of much of their member’s social activity data through APIs, now makes aggregation and therefore search of this activity data possible. Social Search isn’t just a relevancy issue. Social search is the search of this aggregate social member activity data.
Whereas traditional search engines spider and index what tends to be relatively static data, a social search engine aggregates social activity data. The operative word is activity. It is a social member’s activity that is most relevant to social search. Social activity data includes the blogosphere but is not limited to the blogoshpere. Social activity data includes anything from blog posts, to diggs and stumbles and tweets to the many other online social community activities that take place.
Unlike the traditional definition of social search, where social activity determines relevance, under this proposed definition of Social Search, social activity drives the results. Social activity isn’t just a factor in determining relevancy. Social activity makes up the data set.
Social search is exciting because it brings us closer to receiving personal recommendations and insights into topics. This type of personal recommendation already occurs, on social networks in different ways. For example, you can submit a question on LinkedIn’ Answers and within minutes receive a number of answers to your question, or you can join one of the many groups that exist on MySpace, Facebook and other social networks.
However, the promise of social search is not that you will have to submit your question to LinkeIn, or join a group on Facebook, to access the knowledge of the social graph. Instead, social search will reach a point where there will be effective and efficient aggregation of the social activity data, such that a social search will result in relevant, personal and up-to-the minute recommendations, opinions and articles about topics from across the entire social graph. The results will filter the personal activities of perhaps 100s of millions of social network users, giving us access to the live, thinking part of the web.
We appear to be witnessing the early stages of social search. This early stage will progress from what the data sets are and how to aggregate and display them to relevancy. Given the massive amount of data on the social web, relevancy will become a critical issue though unlike Google’s current algorithm, it is likely that relevancy will be determined by a persons’ social community reputation across all networks that she belongs to. There are many reputation agggregators on the social web. It is not clear who will come out with the gold standard for reputation management. Whoever achieves that goal may be the company that ultimately drives search on the social web.
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