Abstract

Nowadays, imparting insights and communicating feelings through interpersonal interaction sites has become extremely normal. The primary focus of sentiment analysis is the identification and classification of opinions or feelings expressed in a text. This paper proposes a method for classifying a tweet as positive, negative, or neutral, as well as a method for extracting sentiments from the tweet. Any organization mentioned or tagged in a tweet can benefit greatly from this strategy. Since tweets typically have an unstructured format, we must first convert them into a structured format. In this paper, tweets are resolved during the pre-processing phase, and the Twitter API is used to access tweets through libraries. We also offer additional comparisons and extract alternatives. Tests, apprenticeships, and so on., are compared to determine higher overall performance, and various scoring criteria for various techniques have been developed. Forever perfect UK fake watches for males and females.
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References

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