Abstract-Users today need to express their informational need in a way such that the search results can be further analyzed to directly address the need, instead of merely returning a list of lexical hits. In this paper we address the problem of extracting sentiment metadata related to the user's topic or entity of interest along with the search results. We propose a framework that provides the flexibility of specifying a sentiment related informational need associated with a particular topic of interest, along with the standard keyword query. This information is then used to extract sentiment scores for the expressed entity of interest based on the "hitlist" of most relevant documents returned by the main search query. Our experimental results based on product and movie review datasets, demonstrate the advantages of embedding the sentiment processing within the search engine framework.Index Terms-Sentiment analysis, information retrieval, query framework, text analytics, sentiment aware search.