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The task I want to do is finding the sentiment of some phrases in a group of sentences (not of all the sentences). For example, I have these sentences:

Ended up deciding that a pebble was best. Less charging, more simplistic ui, buttons seem easier for an older person.

And I want to detect these phrases:

  1. less charging
  2. more simplistic UI
  3. easier buttons

I need something that first detects the phrases, and then identifies their sentiments - they are all positive in terms of smart watches for elderly people.

Does the BERT model solve this problem? Or I have to find another tool/technique?

bad_coder
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Shahab Kazemi
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  • The short answer is yes. I suggest you to look at the [HuggingFace](https://huggingface.co/) library and models, there are a bunch that can perform the so called sentiment analysis, something that tells you if a text expresses a positive/neutral/negative sentiment. – SilentCloud Sep 17 '21 at 13:09
  • Please provide enough code so others can better understand or reproduce the problem. – Community Sep 24 '21 at 14:07

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