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- W2290655735 abstract "In this paper we introduce our contribution to the RepLab 2013 - An evaluation campaign for Online Reputation Management Sys- tems challenge. We participated in the filtering and polarity detection subtasks. The task of filtering is to determine whether a tweet is related to an entity. Then we classify tweets into positive, negative or neutral classes from the entity point of view. To solve these problems we em- ployed supervised machine learning techniques. We applied several Twit- ter specific text preprocessing and features engineering methods. Besides supervised methods, we experimented with incorporating clustering in- formation as well. Our system was ranked 2nd in the filtering task and 1st in the polarity detection task." @default.
- W2290655735 created "2016-06-24" @default.
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- W2290655735 date "2013-01-01" @default.
- W2290655735 modified "2023-09-30" @default.
- W2290655735 title "Filtering and Polarity Detection for Reputation Management on Tweets" @default.
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