• Er. A. P. Mohod
• Mr. Adarsh Golghate
• Mr. Amol Pimpalkar
• Mr. Pratik Gondane
• Mr. Shrineet Padade

Using data mining techniques and decision tree algorithms, this study investigates the feasibility of automatically identifying people's personalities based on their digital footprints. Through an analysis of many sources, such as text messages, social media posts, and web browsing activities, our goal is to identify patterns and correlations that align with specific personality traits. Decision tree algorithms provide a solid foundation for comprehending these connections and enable the development of predictive models that accurately classify personality traits. Important components of the study methodology include feature selection, data collecting, preprocessing, model building, and evaluation. This study addresses a number of ethical issues, including consent, privacy, and fairness. The outcomes show the efficacy and use of automated personality classification across a range of industries, while also highlighting the importance of moral principles and openness controls in data-driven research. All in all, this research expands our understanding of human behaviour in the digital age and opens doors for customised treatments, targeted advertising campaigns, and accelerated recruiting processes.

Automatic Personality Classification, Decision Tree, Data Mining

"Digital Traces Reveal Characteristics: An Analysis of Automated Personality Classification Using Decision Trees and Information Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.c493-c501, April-2024, Available :http://www.jetir.org/papers/JETIR2404256.pdf

"Digital Traces Reveal Characteristics: An Analysis of Automated Personality Classification Using Decision Trees and Information Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppc493-c501, April-2024, Available at : http://www.jetir.org/papers/JETIR2404256.pdf