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Ranking systems are widely used by agencies to rank agents, for example U.S. News & World Report ranks colleges. Such rank-ings are prone to manipulation by the agency (e.g. USNews) for publicity, and also by the agents (e.g. colleges) to get a better rank. We analyze the algorithmic aspects of manipulation in linear ranking systems of m agents using n(More)
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