Sentiment Analysis With Long Sequences

By Medium - 2021-03-10

Description

Sentiment analysis is typically limited by the length of text that can be processed by transformer models like BERT. We will learn how to work around this.

Summary

  • However, one of the problems with many of these models (a problem that is not just restricted to transformer models) is that we cannot process long pieces of text.
  • One is Europe, where we continue to have financial repression, where the ECB continues to buy up to the max in order to minimize spreads between the north and the south — the strong balance sheets and the weak ones — and at some point somebody will have to pay the price for that, but in the short term I don’t see any spike in interest rates,” Bäte said, adding that the situation is different stateside.
  • “ From here, we can see that we get a set of three activation values for each chunk.
  • Finally, we take the mean of the values in each class (or column) to get our final positive, negative, or neutral sentiment probability.

 

Topics

  1. NLP (0.32)
  2. Stock (0.14)
  3. Backend (0.08)

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