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Frequency Matrix Based Summaries of Negative and Positive Reviews


Almuhannad Sulaiman Alorfi


Vol. 23  No. 3  pp. 101-109


This paper discusses the use of sentiment analysis and text summarization techniques to extract valuable information from the large volume of user-generated content such as reviews, comments, and feedback on online platforms and social media. The paper highlights the effectiveness of sentiment analysis in identifying positive and negative reviews and the importance of summarizing such text to facilitate comprehension and convey essential findings to readers. The proposed work focuses on summarizing all positive and negative reviews to enhance product quality, and the performance of the generated summaries is measured using ROUGE scores. The results show promising outcomes for the developed methods in summarizing user-generated content.


Matrix Based Summaries, Negative and Positive Reviews