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Ranking Tweets Considering Trust and Relevance Srijith Ravikumar , Raju Balakrishnan, Subbarao Kambhampati srijith@asu.

Ranking Tweets Considering Trust and Relevance Srijith Ravikumar , Raju Balakrishnan, Subbarao Kambhampati srijith@asu.edu rajub@asu.edu rao@asu.edu. Future Work. Spread of false information reduces the usability of Microblogs . We Model the Tweet eco-system as a tri-layer graph.

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Ranking Tweets Considering Trust and Relevance Srijith Ravikumar , Raju Balakrishnan, Subbarao Kambhampati srijith@asu.

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  1. Ranking Tweets Considering Trust and Relevance SrijithRavikumar, Raju Balakrishnan, Subbarao Kambhampati srijith@asu.edurajub@asu.edu rao@asu.edu FutureWork Spread of false information reduces the usability of Microblogs. We Model the Tweet eco-system as a tri-layer graph. CompletedWork Future Work Top-k Relevance Comparison • How do we rank tweets considering trustworthiness and relevance? • Surface web uses hyperlink analysis between the pages. • Twitter consider retweets as “links” between the tweets for ranking. Build Implicit links between the tweets containing the same fact, and analyze the link-structure. Tweeted URL Tweeted By Top-k Trust Comparison Retweets are sparse, and often planted or passively retweeted. • Agreement-edge weights between the tweets are computed using the Soft TF-IDF with Jaro-Winkler similarity. • Ranking-score is equal to sum of the edge weights. Followers Hyperlinks

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