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Title: Mood Swing Analyser: A Dynamic Sentiment Detection Approach
Authors: Kalyani
Gupta, Ekta
Rathee, Geetanjali
Kumar, Pardeep
Chauhan, Durg Singh
Keywords: Mood Swing
Cyber depression
Issue Date: 2014
Publisher: Jaypee University of Information Technology, Solan, H.P.
Abstract: This paper presents the mood swing analyzer— a novel dynamic sentiment analysis approach that determines the swings in the mood of its user by following a purely unsupervised machine learning technique. This approach uses an internal model to detect the polarity of the sentiments automatically and classify them into clusters based on K-means algorithm hence eradicating the need for normalization. In reaction to a high deviation in the users mood obtained the concept of appropriate message dropping has been proposed. Detailed algorithmic explanation along with the experimental results is well illustrated in this paper. This paper also discusses an extension of this approach in the real world to stop suicidal attempts due to cyber depression.
Appears in Collections:Journal Articles

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