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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM46442
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This paper presents a novel AI-driven framework for personality prediction and career recommendation using insights derived from social media posts. By leveraging Natural Language Processing (NLP) and machine learning techniques, our system analyzes users’ linguistic patterns, sentiment, and behavioral traits to predict their personality based on established psychological models such as the Big Five. Furthermore, we employ a recommendation algorithm to suggest optimal career paths by mapping personality traits to suitable professions using industry-specific datasets. We evaluate our model on real-world social media datasets, comparing its predictive accuracy with traditional psychometric assessments. The findings indicate that AI-based personality assessment can offer a scalable and automated alternative to conventional career counseling, enhancing career decision-making through data-driven insights.Additionally, this technology can be applied to targeted advertising by tailoring content based on personality profiles and to personalized learning by recommending educational resources aligned with an individual’s cognitive style and career aspirations.
KEYWORDS
Publication Date
4/29/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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