Machine Learning and Semantic Sentiment Analysis based Algorithms for Suicide Sentiment Prediction in Social Networks-Reference-Cited by-同舟云学术

Machine Learning and Semantic Sentiment Analysis based Algorithms for Suicide Sentiment Prediction in Social Networks

Published:2017 Issue: Volume:113 Page:65-72
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Birjali Marouane,Beni-Hssane Abderrahim,Erritali Mohammed

Publisher

Elsevier BV

Subject

General Engineering

Reference28 articles.

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3. Gonzalez-Marron D., Mejia-Guzman D., Enciso-Gonzalez A. (2017) Exploiting Data of the Twitter Social Network Using Sentiment Analysis. In: Sucar E., Mayora O., Munoz de Cote E. (eds) Applications for Future Internet. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 179. Springer, Cham.

4. Birjali M., Beni-Hssane A., Erritali M. (2017) A Method Proposed for Estimating Depressed Feeling Tendencies of Social Media Users Utilizing Their Data. In: Abraham A., Haqiq A., Alimi A., Mezzour G., Rokbani N., Muda A. (eds) Proceedings of the 16th International Conference on Hybrid Intelligent Systems (HIS 2016). HIS 2016. Advances in Intelligent Systems and Computing, vol 552. Springer, Cham.

5. Kasturi D. V., Nurhafizah T. Suicide detection system based on Twitter. Science and Information Conference 2014, pp. 785-788, August 27-29, London, UK.

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