Sentiment analysis for depression detection on social networks
Paper
Paper/Presentation Title | Sentiment analysis for depression detection on social networks |
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Presentation Type | Paper |
Authors | Tao, Xiaohui (Author), Zhou, Xujuan (Author), Zhang, Ji (Author) and Yong, Jianming (Author) |
Editors | Li, Jinyan, Li, Xue, Wang, Xue, Li, Jianxin and Sheng, Quan Z. |
Journal or Proceedings Title | Lecture Notes in Artificial Intelligence (Book series) |
ERA Conference ID | 43204 |
Journal Citation | 10086, pp. 807-810 |
Number of Pages | 4 |
Year | 2016 |
Place of Publication | Switzerland |
ISBN | 9783319495859 |
9783319495866 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-319-49586-6_59 |
Web Address (URL) of Paper | http://link.springer.com/chapter/10.1007/978-3-319-49586-6_59 |
Conference/Event | 12th International Conference on Advanced Data Mining and Applications (ADMA 2016) |
International Conference on Advanced Data Mining and Applications | |
Event Details | International Conference on Advanced Data Mining and Applications ADMA Rank B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B |
Event Details | 12th International Conference on Advanced Data Mining and Applications (ADMA 2016) Event Date 12 to end of 15 Dec 2016 Event Location Gold Coast, QLD, Australia |
Abstract | 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. |
Keywords | sentiment analysis, depression, social networks |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
460612. Service oriented computing | |
420308. Health informatics and information systems | |
420313. Mental health services | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | School of Agricultural, Computational and Environmental Sciences |
School of Management and Enterprise | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q3w32/sentiment-analysis-for-depression-detection-on-social-networks
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