Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
Models of social groups in blogosphere based on information about comment addressees and sentiments
SocInfo'12 Proceedings of the 4th international conference on Social Informatics
RBEM: a rule based approach to polarity detection
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
Cross-lingual polarity detection with machine translation
Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining
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We present the system for automated sentiment analysis on multilingual user generated content from various social media and e-mails. One of the main goals of the system is to make people aware how much positive and negative content they read and write. The output is summarized into a database allowing for basic OLAP style exploration of the data across basic dimensions including for example time and correspondents dimensions. The sentiment analysis is based on a four-step approach including language identification for short texts, part-of-speech tagging, subjectivity detection and polarity detection techniques. We extensively tested our system on data from Twitter, Face book and Hyves. We also developed an MS Outlook sentiment analysis plug-in allowing people to see how positive or negative the content of the e-mails is and provide confirmatory or correcting feedback on the correctness of the sentiment classification at the sentence or e-mail level.