Evaluation of Machine Learning Techniques for Enhancing Scholarship Schemes Using Artificial Emotional Intelligence
DOI:
https://doi.org/10.4108/eetiot.5368Keywords:
Emotion AI, Opinion Mining, SentiwordNet, WordNet, Sentiment Polarity ClassificationAbstract
This paper investigates the sentiment analysis of the” scholarship system” [4], in Odisha, primarily, to identify why some students do not apply for government-sponsored scholarships. Our research focuses on social media platforms, surveys, and machine learning-based analyses to understand the decision-making process and increase awareness about the various scholarship schemes. The goal of our experiment is to determine the efficacy of sentiment analysis in evaluating the effectiveness of different scholarship schemes. A wide variety of techniques based on dictionaries; corpora lexicons are used in different scholarship schemes for sentiment analysis. Our research paper is based on an evaluation process that could have a positive effect on the government by improving scholarship programs and giving financial aid to students from poor families, which would raise the level of education in Odisha. Our research paper concludes with a summary of successful and unsuccessful schemes, as well as their Word frequency counts and Sentiment Polarity scores.
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