anhthuan1999/Vietnamese-News-Classification
We use LSTM, BiLSTM, BERT and SVM with TF-IDF, Word2vec and Bag-of-words to classify this documents to positive (labeled as 1), neutral (labeled as 0) and negative (labeled as 2)
This helps businesses and individuals understand public sentiment expressed in Vietnamese news articles and comments. By inputting raw Vietnamese text from news sources, it outputs a classification indicating whether the sentiment is positive, neutral, or negative. This tool is useful for market researchers, brand managers, or public relations professionals tracking public opinion in Vietnam.
No commits in the last 6 months.
Use this if you need to quickly gauge the emotional tone of a large volume of Vietnamese news content and associated comments.
Not ideal if you require nuanced sentiment analysis beyond positive, neutral, or negative, or if your content is not primarily news-based Vietnamese text.
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Jupyter Notebook
License
MIT
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Last pushed
Sep 26, 2023
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