Sentiment Analysis for Customer Review: Case Study of Traveloka

This repository dataset contains 1.200 tweets that are related to our paper Sentiment analysis for customer review: Case study of Traveloka - ScienceDirect. It is labeled into two classes: negative and positive.

Which dataset should I use?

We recommend using the data_traveloka_fix as the other two files are just test files and are not meant to be used.

Data Formats

The file starts with a header, and each following line consists of a tweet followed by its respective label separated by a pipe ( | ). We used to quote (" ") inside the text to avoid column separation.

Citation

If you use this dataset in a scientific publication, we would appreciate using the following citations:

Plain Text

Diekson, Z. A., Prakoso, M. R. B., Putra, M. S. Q., Syaputra, M. S. A. F., Achmad, S., & Sutoyo, R. (2023). Sentiment analysis for customer review: Case study of Traveloka. Procedia Computer Science, 216, 682-690.

BibTeX

@article{diekson2023sentiment,
  title={Sentiment analysis for customer review: Case study of Traveloka},
  author={Diekson, Ziedhan Alifio and Prakoso, Muhammad Rivyan Bagas and Putra, Muhammad Savio Qalby and Syaputra, Muhammad Shaden Al Fadel and Achmad, Said and Sutoyo, Rhio},
  journal={Procedia Computer Science},
  volume={216},
  pages={682--690},
  year={2023},
  publisher={Elsevier}
}