Sentiment analysis for depression detection on social networks

Tao, Xiaohui and Zhou, Xujuan and Zhang, Ji and Yong, Jianming (2016) Sentiment analysis for depression detection on social networks. In: 12th International Conference on Advanced Data Mining and Applications (ADMA 2016), 12-15 Dec 2016, Gold Coast, QLD, Australia .


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.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to published version, in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 16 Feb 2017 07:45
Last Modified: 04 Jun 2017 23:43
Uncontrolled Keywords: sentiment analysis, depression, social networks
Fields of Research : 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0805 Distributed Computing > 080505 Web Technologies (excl. Web Search)
08 Information and Computing Sciences > 0807 Library and Information Studies > 080702 Health Informatics
11 Medical and Health Sciences > 1117 Public Health and Health Services > 111714 Mental Health
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
E Expanding Knowledge > 97 Expanding Knowledge > 970111 Expanding Knowledge in the Medical and Health Sciences
Identification Number or DOI: 10.1007/978-3-319-49586-6_59

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