nlp.cs.aueb.gr: Two Stage Sentiment Analysis
نویسندگان
چکیده
This paper describes the systems with which we participated in the task Sentiment Analysis in Twitter of SEMEVAL 2013 and specifically the Message Polarity Classification. We used a 2-stage pipeline approach employing a linear SVM classifier at each stage and several features including BOW features, POS based features and lexicon based features. We have also experimented with Naive Bayes classifiers trained with BOW features.
منابع مشابه
AUEB: Two Stage Sentiment Analysis of Social Network Messages
This paper describes the system submitted for the Sentiment Analysis in Twitter Task of SEMEVAL 2014 and specifically the Message Polarity Classification subtask. We used a 2–stage pipeline approach employing a linear SVM classifier at each stage and several features including morphological features, POS tags based features and lexicon based features.
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