document: Answering search queries with CrowdSearcher Web users are increasingly relying on social interaction to complete and validate the results of their search activities . While search systems are superior machines to get world-wide information , the opinions collected within friends and expert\/local communities can ultimately determine our decisions : human curiosity and creativity is often capable of going much beyond the capabilities of search systems in scouting `` interesting '' results , or suggesting new , unexpected search directions . Such personalized interaction occurs in most times aside of the search systems and processes , possibly instrumented and mediated by a social network ; when such interaction is completed and users resort to the use of search systems , they do it through new queries , loosely related to the previous search or to the social interaction . In this paper we propose CrowdSearcher , a novel search paradigm that embodies crowds as first-class sources for the information seeking process . CrowdSearcher aims at filling the gap between generalized search systems , which operate upon world-wide information - including facts and recommendations as crawled and indexed by computerized systems - with social systems , capable of interacting with real people , in real time , to capture their opinions , suggestions , emotions . The technical contribution of this paper is the discussion of a model and architecture for integrating computerized search with human interaction , by showing how search systems can drive and encapsulate social systems . In particular we show how social platforms , such as Facebook , LinkedIn and Twitter , can be used for crowdsourcing search-related tasks ; we demonstrate our approach with several prototypes and we report on our experiment upon real user communities .
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