Topic Modeling for Unsupervised Learning

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Topic modeling is one of the most powerful techniques of unsupervised learning🤖 Let's implement a topic modeling pipeline without going into heavy statistics behind it⚡ A 🧵👇

This thread is derived from my newest article on Cyberbullying detection using Topic modeling and sentiment analysis Check out the article for a more detailed explanation with code👇 analyticsvidhya.com/blog/2023/03/detect-cyberbullying-using-topic-modeling-and-sentiment-analysis/

1) Load the Twitter dataset Pre-process the dataset using lemmatization and stop word removal Check out the full article + code using the below link: analyticsvidhya.com/blog/2023/03/detect-cyberbullying-using-topic-modeling-and-sentiment-analysis/

2) Select the corpora from the Twitter dataset Write the preprocess function in a pythonic way🐍

3) Setting up a topic model pipeline We have used the LDA model from the gensim library See the code below👇

4) Visual Interpretation of Topic Modeling Output

The output of the above code👇

Check out the full article + code using the below link: Don't forget to share your feedback on the same analyticsvidhya.com/blog/2023/03/detect-cyberbullying-using-topic-modeling-and-sentiment-analysis/

Check out the github repository for more👇 Feel free to raise an issue if you find one github.com/avikumart/Cyberbullying-Detection-NLP

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