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Tweet sentiment analysis using deep learning with nearby locations as features

  • Wei Lun Lim
  • Chiung Ching HoEmail author
  • Choo-Yee Ting
Conference paper
  • 527 Downloads
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 603)

Abstract

Twitter classification using deep learning have shown a great deal of promise in recent times. Many works had been performed on twitter sentiment analysis but there has not been much work done investigating the effects of location on twitter sentiment analysis. In this study, we concatenated text and location features as a feature vector for twitter sentiment analysis using a deep learning classification approach specifically Convolutional Neural Network (CNN). The achieved results show that using location as a feature alongside text has increased the sentiment analysis accuracy.

Keywords

sentiment analysis location analysis natural language understanding deep learning convolutional neural network 

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Notes

Acknowledgements

This project is partially supported by Artificial Intelligence Research Unit (AiRU).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Computing & InformaticsMultimedia UniversityCyberjayaMalaysia

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