Finding the Best Source of Information by means of a Socially-enabled Search Engine

In the era of Web 2.0, users strongly contribute to blogs, providing their opinions and useful information about specific topics; typically, users that are interested in a topic looks for related blogs in pull mode. But social networks have become even more effective in dis- seminating opinions and information in push mode, because users directly receive tweets and posts. In this context, what is the best source of information ? That is, what is the best blog with useful contribution about a given topic, expressed by a non trivial user query ? Furthermore, what is the Tweeter user that sent the best contributions about a given topic ? We think that a solution to this new emerging problem is a novel class of search engines, that we can call Socially-enabled Search Engines, i.e., search engines that exploit social contributions to rank sources of infor- mation. In this paper, we present the prototype search engine we are developing: in particular, we present the main ideas, the retrieval model and the query engine of our prototype.