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nrc-emotion-lexicon

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This project uses machine learning to categorize and prioritize airline user tweets based on content and sentiment. The goal is to reduce airlines' workload and provide personalized, empathetic responses to users. By training a sentiment analysis model, airlines can better understand customers' needs and improve their overall service on Twitter.

  • Updated Apr 11, 2022
  • HTML

In the present day, the entertainment industry is constantly evolving toward making the most enjoyable and profitable sources of film entertainment. Through the use of movie rating sites, we can now decide whether or not it is worth the trip to the movie theatre to watch a partiuclar film. With this in mind, I wanted to explore what aspects of m…

  • Updated Sep 21, 2020
  • Python

The system is implemented to scrape data from a booking website, perform Emotion Analysis on the reviews of the selected hotel and visualized the result over a time axis. R is used to implement the system and Shiny library is used to develop the Front-end.

  • Updated Jun 6, 2020
  • R

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