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Sentiment Analysis for Depression Detection on Social Networks - 2016

Research Area:  Machine Learning


As a response to the urgent demand of methods that help detect depression at early stage, the work presented in this paper has adopted sentiment analysis techniques to analyse users contributions of social network to detect potential depression. A prototype has been developed, aiming at demonstrating the mechanism of the approach and potential social effect that may be delivered. The contributions include a depressive sentiment knowledge base and an algorithm to analyse textual data for depression detection.

Author(s) Name:  Xiaohui Tao, Xujuan Zhou, Ji Zhang & Jianming Yong

Journal name:  

Conferrence name:  Advanced Data Mining and Applications

Publisher name:  Springer

DOI:  10.1007/978-3-319-49586-6_59

Volume Information: