Aspect-level entity extraction and sentiment analysis

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I am working on Natural Language Processing and having a hard time on analyzing sentiment values on certain entities. For example if i say: "I love the fact that I am finally leaving Chicago", it says that the sentence is a positive sentence. But as you can see it is pretty negative for the entity "Chicago". Anyone knows if there is any related work on this? Thanks in advance

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The key word for this is “targeted sentiment analysis”

There are many articles on it and also code on GitHub.

I’ll update if I find the link for the model I used.

You might need to do some labeling and training for your specific requirements.

Update: https://github.com/songyouwei/ABSA-PyTorch

train data will look like this:

I love the fact that I am finally leaving $T$, Chicago, -1