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Sentiment analysis of X text with deep learning

Om Sentiment analysis of X text with deep learning

Sentiment analysis is one of the text classification applications of natural language processing, basically assigning an appropriate category to the content of a sentence, text or document, based on the (previously unstructured) text processing. This classification is done by assigning a sentiment polarity: positive, negative or neutral to a sentence or a document, or by assigning an emotion that is identified in the sentence.Sentiment analysis is currently a powerful tool in various applications for different industries. It can be applied to different sectors; textile, automotive, food, manufacturing, etc., or even in government agencies, universities, among others, but specifically in spaces where data is collected on a daily basis. Therefore, the use of this type of strategies is becoming more and more important. From the data that have been generated and stored for years, inferences can be made to help validate, support or stop any type of decision making.

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  • Språk:
  • Engelska
  • ISBN:
  • 9786207034284
  • Format:
  • Häftad
  • Sidor:
  • 84
  • Utgiven:
  • 10. januari 2024
  • Mått:
  • 150x6x220 mm.
  • Vikt:
  • 143 g.
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Leveranstid: 2-4 veckor
Förväntad leverans: 10. december 2024

Beskrivning av Sentiment analysis of X text with deep learning

Sentiment analysis is one of the text classification applications of natural language processing, basically assigning an appropriate category to the content of a sentence, text or document, based on the (previously unstructured) text processing. This classification is done by assigning a sentiment polarity: positive, negative or neutral to a sentence or a document, or by assigning an emotion that is identified in the sentence.Sentiment analysis is currently a powerful tool in various applications for different industries. It can be applied to different sectors; textile, automotive, food, manufacturing, etc., or even in government agencies, universities, among others, but specifically in spaces where data is collected on a daily basis. Therefore, the use of this type of strategies is becoming more and more important. From the data that have been generated and stored for years, inferences can be made to help validate, support or stop any type of decision making.

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