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Ranking documents with respect to users' information needs is a challenging task, due, in part, to the dynamic nature of users' interest with respect to a query, which can change over time. In this paper, we propose an innovative method for characterizing the interests of a community of users at a specific point in time and for using this characterization to alter the ranking of documents retrieved for a query. By generating a community interest vector (CIV) for a given query, we measure the community interest by computing a score in a specific document or web page retrieved by the query. This score is based on a continuously updated set of recent (daily or past few hours) user-oriented text data. When applying our method in ranking Yahoo! Buzz results, the CIV score improves relevant results by 16% as determined by real-world user evaluation.