Twitter has become a prime source for disseminating news and opinions. However, the length of tweets prohibits detailed descriptions; instead, tweets sometimes contain URLs that link to detailed news articles. In this paper, we devise generic techniques for recommending tweets for any given news article. To evaluate and compare the different techniques, we collected tens of thousands of tweets and news articles and conducted a user study on the relevance of recommendations.
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