sakshidgoel/Bilingual-Sentiment-Analysis
The main aim of the project is to develop a sentiment analyzer that can be used on twitter data to classify it as positive or negative. Our project takes care of the challenge of bilingual comments, where people tweet in two languages, in this case Hindi and English, in the Latin Alphabet.
This project helps social media analysts and marketers understand public opinion from Twitter data that mixes Hindi and English. It takes tweets written in a combination of these two languages and classifies their overall sentiment as positive or negative. The output helps users quickly gauge the emotional tone of conversations and trends among a bilingual audience.
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Use this if you need to perform sentiment analysis on Twitter data that frequently contains mixed Hindi and English text, and you want to classify those tweets as positive or negative.
Not ideal if your data is in a single language, or if it involves other languages besides Hindi and English, or if you require more nuanced sentiment categories than just positive or negative.
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May 19, 2020
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