Abstract: Personality prediction from text data, particularly from social media posts, has gained significant attention due to its wide- ranging applications in various fields such as psychology, marketing, and personalized recommendation systems. This study presents a machine learning approach for predicting personality types based on text data extracted from social media posts, focusing on Twitter. The study employs a state-of-the-art natural language processing (NLP) technique, namely BERT (Bidirectional Encoder Representations from Transformers), to encode and understand the textual content. BERT is a transformer-based model known for its effectiveness in capturing contextual information from text data. The Twitter API is utilized to retrieve a user's recent tweets, which serve as input for the personality prediction model. The preprocessing pipeline involves text cleaning steps to remove noise such as special characters, URLs, and punctuation marks....
Cite:
P.R. Krishna Prasad, Naga Sai Ajay Kumar Abburi, Pavan Sai Ganesh Cherukuri, Dheeraj Kumar Bhattu, Jaswanth Gadde, "Unveiling Personality Traits through Social Media Language Analysis: A Novel Approach using Language Models", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 3, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13326.
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DOI:
10.17148/IJARCCE.2024.13326
