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This research aims to explore public sentiment regarding specific topics by analyzing Twitter data using machine learning.

April 27, 2026Open Access

Sentimental Analysis of Twitter Data using Machine Learning

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This research aims to explore public sentiment regarding specific topics by analyzing Twitter data using machine learning.
Utilized machine learning and natural language processing techniques for sentiment classification.
Preprocessed Twitter data by removing URLs, punctuation, and irrelevant characters to enhance accuracy.
Applied sentiment polarity scoring and data visualizations to analyze and present findings on public sentiment.
Predominance of positive sentiments suggests a generally favorable public perception; specific metrics were not quantified.
Recognition of negative sentiments offers contrasting views, revealing diversity in opinions.
Findings highlight key periods of sentiment change and specific topics driving positive or negative reactions.

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Randomized trial analyzes public sentiment using machine learning on Twitter data, highlighting trends and perceptions.

Reddy et al. (2026) studied this question.

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