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A sentimental analysis of data from Twitter regarding customer sentiment for 6 US airlines: American, Delta, Southwest Airlines, United, US Airways, and Virgin America. Then use Tensor Flow to predict the chance of a tweet to be positive, negative, or neutral.

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Rino04/Sentimental-Analysis-of-USA-Airlines

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Sentimental-Analysis-of-USA-Airlines

The project is an analysis of data from Twitter regarding customer sentiment for 6 US airlines: American, Delta, Southwest Airlines, United, US Airways, and Virgin America.Then use Tensor Flow to predict the chance of a tweet to be positive,negative or neutral.. This project seeks to predict if a tweet if negative or positive using neural networks. The analysis have been conducted using tensorflow keras.

Motivation

This is project was done as part of a data science course.

Platform Used:

Google Collab Wandb Github

Summary of Analysis

  1. Defining the Question
  2. Reading the Data.
  3. Checking the Data.
  4. Data Cleaning
  5. Merging the Dataframes
  6. Performing EDA
  7. Prediction Models
  8. Evaluation of the solution
  9. Challenging the solution
  10. Conclusion

Setup

To easily use this code you need: Google colab or Jupyter Notebook importation of pandas, numpy, tensorflow,nlkt and wordcloud

Team Members

  1. Jackson Kyalo
  2. Dennis Kiarie
  3. Brian Muchira
  4. Iyline Chumo

Contact Details

Incase of enquiries,additional suggestions or concerns,get in touch. jackkyalo978@gmail.com

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A sentimental analysis of data from Twitter regarding customer sentiment for 6 US airlines: American, Delta, Southwest Airlines, United, US Airways, and Virgin America. Then use Tensor Flow to predict the chance of a tweet to be positive, negative, or neutral.

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