Personality Identification from Social Media Using Deep Learning: A Review

6Citations
Citations of this article
43Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed.

Cite

CITATION STYLE

APA

Bhavya, S., Pillai, A. S., & Guazzaroni, G. (2020). Personality Identification from Social Media Using Deep Learning: A Review. In Advances in Intelligent Systems and Computing (Vol. 1057, pp. 523–534). Springer. https://doi.org/10.1007/978-981-15-0184-5_45

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free