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In this paper, we propose a method to predict the user emotional state (anger or neutral) for improvement of user satisfaction in call center. In order to detect the user satisfaction more accurately, our work employs the following information fusion technologies: (1) in view of the data imbalance problem, we adopt statistical model fusion, (2) for improving classifier performance, we combine features...
We present a machine learning approach to sentiment classification on twitter messages (tweets). We classify each tweet into two categories: polar and non-polar. Tweets with positive or negative sentiment are considered polar. They are considered non-polar otherwise. Sentiment analysis of tweets can potentially benefit different parties, such as consumers and marketing researchers, for obtaining opinions...
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