Predicting Personality Traits of Introverts and Extroverts for Forensic Applications

• Published in: 2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE) pp. 252 - 257
• Main Authors: Kumar, Mandeep, Sirohi, Ramesh, Kushwaha, Pramadvara, Gulhane, Monali, Singh, Manvendra, Kumar, Ketan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 09.05.2024
• Subjects: Accuracy; Analytical models; extrovert; forensic studies; introvert; Machine learning; MBTI; mental analysis; Neural networks; Prediction algorithms; Predictive models; psychological state; Psychology; Social networking (online)
• DOI: 10.1109/IC3SE62002.2024.10593431

With the recent trends in social media networks, it is necessary to identify personality traits as social media platforms have become a necessary component of our lives. This knowledge is crucial for many areas like law enforcement, security, and marketing, where customer behaviour insight is paramount. Research on personality recognition from social media data is a crucial link between online activities and their real-world consequences, aiding in a more profound comprehension of human behaviour in the digital era. The research proposed the detection of personality traits in introvert and extrovert categories using the Myers-Brigger Typer Indicator dataset. The research focuses on the need to analyze the psychological aspect of forensic studies. The research uses different machine learning algorithms to focus with the highest accuracy on the proposed prediction, and the neural network with keras achieves an accuracy of 99%. The findings are tangible to the need for forensic study by analysis of the psychological status of the person.