Artificial Intelligence application for the analysis of personality traits and disorders in social media: A Survey

Author:

Ellouze Mourad1,Hadrich Belguith Lamia2

Affiliation:

1. LITL, Lille Catholic University, Lille, France

2. MIRACL, University of Sfax Faculty of Economics and Management of Sfax, Sfax, Tunisia

Abstract

Personality analysis has a positive influence on humanity as it aids in identifying personality traits and disorders. In addition, it facilitates the monitoring of cases and enriches doctors’ knowledge bases, particularly in decision-making processes. This study includes a comprehensive literature review on personality analysis approaches from social media, aiming to gain a thorough understanding of the current studies on personality therapy. Moreover, the objective of this study is to identify various limitations present in these studies and explore potential avenues for enhancement. More specifically, this research begins with an introduction that discusses the main concepts of traits and personality disorders, as well as the importance of psychological analysis. Following that, four cluster studies related to personality analysis on social media are presented: personality traits, personality disorders, detection of links between diseases, and monitoring patient status. Then, the majority of the currently available works for each cluster are exposed. Afterward, a comparative study of the different presented works is proposed. Finally, an outline of plans for further research in this area is provided, detailing potential paths for exploration.

Publisher

Association for Computing Machinery (ACM)

Reference95 articles.

1. Moving beyond DSM5 and ICD11: Acoustic analysis for psychological stress on daily-wage workers in India during COVID19;Agarwal Ajay;Computers in Human Behavior Reports,2021

2. Nadeem Ahmad and Jawaid Siddique. 2017. Personality assessment using Twitter tweets. Procedia computer science 112 (2017), 1964–1973.

3. Salwa Al Majali. 2020. The digital world for children and its relationship with personality disorders: Exploring emerging technologies. International Journal of Emerging Technologies in Learning (iJET) 15 1(2020) 213–221.

4. Transfer learning for Arabic named entity recognition with deep neural networks;Al-Smadi Mohammad;Ieee Access,2020

5. Andry Alamsyah, Rafa Syafiq Bastikarana, Alya Rysda Ramadhanti, and Sri Widiyanesti. 2020. Recognizing Personality from Social Media Linguistic Cues: A Case Study of Brand Ambassador Personality. In 2020 8th International Conference on Information and Communication Technology (ICoICT). IEEE, 1–5.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3