Sentiment analysis using Machine Learning (Vader Lexicon)
Sentiment analysis, also known as opinion mining, is a natural language processing (NLP) technique that involves determining the sentiment or emotional tone expressed in a piece of text. The goal of sentiment analysis is to understand and categorize the subjective opinions or feelings conveyed in the text as positive, negative, or neutral.
VADER (Valence Aware Dictionary and Sentiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is designed for analyzing text data to determine the sentiment expressed. Developed by researchers C.J. Hutto and Eric Gilbert, VADER is particularly popular for its ease of use and its ability to quickly analyze sentiment without the need for extensive training data.
Github_Repository : https://github.com/asishrj91/Sentimen...
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