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A Comprehensive Study of Automated Author Profiling Techniques for Personality Trait Detection

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A Comprehensive Study of Automated Author Profiling Techniques for Personality Trait Detection Turkish Journal of Physiotherapy and Rehabilitation; 32(3) ISSN 2651-4451 | e-ISSN 2651-446X A COMPREHENSIVE STUDY OF AUTOMATED AUTHOR PROFILING TECHNIQUES FOR PERSONALITY TRAIT DETECTION Aparna M C 1, Dr M.N. Nachappa2 1Research Scholar,School of Computer Science and Information Technology, JAIN( Deemed to be University), Bangalore [email protected] 2Professor and Head, School of Computer Science and Information Technology, JAIN (Deemed to be University), Bangalore [email protected] ABSTRACT The features of an individual's behaviour, motivation, emotion, and cognitive pattern make up their personality. Our personality has a big influence on us and consequently has an impact on our life, physical well-being, work choices, and health. [1]. The method of determining the user's demographic traits such as age group, gender, native language, educational qualification, personality trait, and dialect is called Author Profiling (AP)[2]. Much research has been going on in the above field as there are many applications in different areas like marketing, cybercrime, etc. Moreover, there has been much progress as Machine learning and Deep learning classifiers like Support Vector Machine, M5 Regression, CNN, RNN, and many more are being used for automatic classification. This paper describes significant machine learning and deep learning models on Author Profiling for Personality detection along with an extensive study on current research trends, challenges, and applications of detecting personality traits of an author of the text. Keywords: Author Profiling, Big 5 personality traits, Text Classification. I. INTRODUCTION Individuals' choice of words and how they use words convey a share of information about the individual and hint at their age, social status, sex, personality and motives[3]. Hence to know whether a person is emotionally distant or close, shallow or thoughtful, neurotic, extraverted or open to new types of experience can be sensed by the words used by that person. Moreover, one can analyse and access large volumes of text samples to identify the personality traits of authors automatically and predict their potential responses and behaviours [4]. Machine learning (ML) algorithms are extensively used in a rapidly improving digital world to detect relevant patterns from data which is surrounding us human beings. Thus, Author profiling aims to find complete information about a person by analysing texts written by that person using ML or Deep Learning techniques[5]. This study has extensive applications in security of digital data, spotting predatory internet activities, cyber-terrorism and detecting fraud, or even plagiarism. It is also used in more familiar settings like market research, chatbots and diagnosis and also improving service of the customer[6]. This paper presents a survey of how automated personality trait detection methodologies have progressed through the years. We have covered the base for measurement of Personality Traits in Section II, followed by Section III, covering various study applications. Section IV gives a detailed explanation of the datasets available for the study of AP. Section V analyzes the current research trends in AP for personality traits using Machine learning and Deep learning along with their methodologies. Finally, Sections VI and VII describe the various challenges and conclusions, respectively. Personality trait measures: While personality theory remains predominant with its own set of disputes, researchers have primarily concentrated to the Big-5 trait personality model over the last few decades. Numerous additional traits are being fused into the Big-5 trait model for entrepreneurial work, including innovativeness, self-efficacy, risk attitudes and locus of control. Thus, personality traits are very helpful in determining one's outcomes of life. www.turkjphysiotherrehabil.org 10891 Turkish Journal of Physiotherapy and Rehabilitation; 32(3) ISSN 2651-4451 | e-ISSN 2651-446X A personality trait is a usual outline of thinking, feeling or behaving that have a tendency to be constant over the time and across various similar situations [7]. The languages we have around us include various adjectives to describe personality, among these many of them can be arranged in the class of the Big Five trait dimensions: a) Extroversion (e.g., friendly, energetic and assertive). b) Agreeableness (e.g., compassionate, respectful, and trusting). c) Conscientiousness (e.g., orderly, hardworking, and responsible) d) Neuroticism (worrying, temperamental and pessimistic) e) Openness to Experience (intellectual, artistic, imaginative and Open-Mindedness) A great number of interpersonal, individual and social-institutional outcomes have been associated with the Big 5 personality traits; this association has been proved with the literature reviews conducted to date[5]. For example, high extroversion has been related to capacity of leadership and status is society, Conscientiousness has been connected to health and job performance, Agreeableness has been associated with satisfaction in a relationship and volunteerism, Neuroticism had been related to negative emotionality and conflict in relationship while open mindedness is linked to political liberalism and spirituality[8]. As widely held research uses the Big-Five personality trait measurement for classification, we considered the above method for analysis and measurement of model accuracies. II. APPLICATIONS: Automating the personality recognition systems has a large number of industrial applications in the present times. With the kind of research going on, we can deduce that the market options will rise shortly. The models are expected to measure the personality consistently and accurately. If this is achieved one can expect the increasing demand for automated personality recognition software. Since research in this field is developing, we are certain to find models with more reliability and accuracy. Almost every human to computer interaction in the future can be connected with Artificial intelligence. Many computational devices that are equipped with personality are being developed which can make it react to different people in different ways. For example, we can have a phone that has different modes for people having different personalities, this can lead to more personalized interaction with the device. Personality traits can also be used to achieve higher accuracy in tasks such as detection of sarcasm, systems for polarity disambiguation of words, or lie detection. Below are the few areas in which personality detection plays a vital role: a) Enhanced Personal Assistants: Automatic detection of the user's personality can help voice assistants that are automated such as Google Assistant, Siri, and Alexa and so on, give customized responses. Also, to increase user satisfaction, these voice assistants can be programmed to display different personalities depending on the person's personality. b) Recommendation Systems: It is said that people who share a specific personality type tend to share similar interests and also hobbies. Thus, positively evaluating various products by another user of a similar personality type can recommend different products and services to a user. For example, Yin et al. gave a proposal to model the intentions of purchases of automobiles by customers depending on their hobbies and personality [9]. In addition, Yang and Huang have successfully developed a game recommendation system for players which recommends games for different players depending on their personality traits that were derived through automated personality detection by analysing their chats with other players[10]. c) Polarity Detection of words: Cambria et al. mention that Personality detection is a subpart of Sentiment analysis, and it can be used for polarity disambiguation of words in finding the sentiment lexicon[11]. Majumdar et al. say that it can also be used for disambiguation between non-sarcastic and sarcastic content[12]. www.turkjphysiotherrehabil.org 10892 Turkish Journal of Physiotherapy and Rehabilitation; 32(3) ISSN 2651-4451 | e-ISSN 2651-446X d) Specialized Health Care and Counselling: People are giving more importance to mental health care than in earlier years. Many individuals are coming up to seek professional counselling to cure mental health- related issues. Personality detection can prove to be very helpful in fixing mental health-related problems, and it helps give better counselling guidance. e) Forensic Science: Determining the linguistic profile of an individual who is the author of a suspicious text can prove to be very helpful to gain some background information about the author. Personality detection models can also help increase the accuracy of lie detectors[13]. f) Job Recruiting: Most of the recruiting process these days concentrates more on the aptitude of the candidate. While it is an essential aspect to search for in the candidate, it is equally important to recruit a candidate who matches the personality required for that job role to perform better in the position given. For example, after the personality detection test, candidates with high neuroticism trait values can be eliminated for positions involving leadership qualities[14]. g) Study of Psychology: Automated detection of personality traits can help in finding strong relations between personality traits of people and their behaviours, knowing this information can be helpful in discovering new dynamics of human spirits. h) Forecasting personality
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