[D] How to best extract product benefits/problems from customer reviews using NLP?

• BERTopic

  22 5,543 8.2 Python

  Leveraging BERT and c-TF-IDF to create easily interpretable topics.

I have experimented a bit with BERTopic but didn't find the results very useful. The issue is, that it is very important what exactly people are liking or disliking about the products, not just the fact that they are talking about specific aspects.

• PyABSA

  2 858 5.3 Jupyter Notebook

  Sentiment Analysis, Text Classification, Text Augmentation, Text Adversarial defense, etc.;

https://github.com/yangheng95/PyABSA - for extraction of aspects + corresponding sentiments

• WorkOS

  workos.com sponsored

  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

• SelSum

  1 44 0.0 Python

  Abstractive opinion summarization system (SelSum) and the largest dataset of Amazon product summaries (AmaSum). EMNLP 2021 conference paper.

https://github.com/abrazinskas/SelSum - for abstractive summarization into vertdict/pros/cons

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