Suicidal Profiles Detection in Twitter

Atika Mbarek, Salma Jamoussi, Anis Charfi, Abdelmajid Ben Hamadou

2019

Abstract

About 800 000 people commit suicide every year and detecting suicidal people remains a challenging issue as mentioned in a number of suicide studies. With the increased use of social media, we witnessed that people talk about their suicide plans or attempts in public on these networks. This paper addresses the problem of suicide prevention by detecting suicidal profiles in social networks and specifically twitter. First, we analyse profiles from twitter and extract various features including account features that are related to the profile and features that are related to the tweets. Second, we introduce our method based on machine learning algorithms to detect suicidal profiles using Twitter data. Then, we use a profile data set consisting of people who have already committed suicide. Experimental results verify the effectiveness of our approachin terms of recall and precision to detect suicidal profiles. Finally, we present a Java based prototype of our work that shows the detection of suicidal profiles.

Paper Citation

in Harvard Style

Mbarek A., Jamoussi S., Charfi A. and Ben Hamadou A. (2019). Suicidal Profiles Detection in Twitter.In Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-386-5, pages 289-296. DOI: 10.5220/0008167602890296

in Bibtex Style

@conference{webist19,
author={Atika Mbarek and Salma Jamoussi and Anis Charfi and Abdelmajid Ben Hamadou},
title={Suicidal Profiles Detection in Twitter},
booktitle={Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2019},
pages={289-296},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008167602890296},
isbn={978-989-758-386-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Suicidal Profiles Detection in Twitter
SN - 978-989-758-386-5
AU - Mbarek A.
AU - Jamoussi S.
AU - Charfi A.
AU - Ben Hamadou A.
PY - 2019
SP - 289
EP - 296
DO - 10.5220/0008167602890296