loading
Papers

Research.Publish.Connect.

Paper

Authors: Atika Mbarek 1 ; Salma Jamoussi 1 ; Anis Charfi 2 and Abdelmajid Ben Hamadou 1

Affiliations: 1 Multimedia InfoRmation Systems and Advanced Computing Laboratory (MIRACL), University of Sfax, Tunisia, Digital Research Center of Sfax DRCS, 3021, Sfax and Tunisia ; 2 Carnegie Mellon University in Qatar, Doha and Qatar

ISBN: 978-989-758-386-5

Keyword(s): Suicide, Twitter, User Profile, Machine Learning.

Related Ontology Subjects/Areas/Topics: Social Media Analytics ; Society, e-Business and e-Government ; Web Information Systems and Technologies

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. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.227.3.146

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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

@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},
}

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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.