Abstract: The sentiment analysis system presented in this project employs a methodology rooted in manual keyword analysis, capitalizing on the inherent associations between specific words and emotional sentiments. For instance, in movie reviews, positive expressions are characterized by terms like "great" and "love," while negative sentiments are often conveyed through words such as "hate" and "awful." By quantifying the frequency of these selected keywords, comprehensive feature vectors are constructed to capture the nuanced sentiment of input data.
Cite:
Anuj Pund, Tanmay Harde, Atul Awasarmol, Siddhant bodele, Prachee Meshram,Dr. P. M. Chaudhari, "Sentiment Analysis of Students Reviews using Natural Language Process", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 1, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13122.
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DOI:
10.17148/IJARCCE.2024.13122
