Sentiment Analysis for Mining Customer Opinion on Twitter: A Case Study of Ride-Hailing Service Provider

Zulkarnian Zulkarnain, Isti Surjandari Prajitno, Reggia Aldiana Wayasti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The function of social media is now transforming to become source of information, even to support electronic word of mouth (e-WOM). Many companies, including ride-hailing service providers, can capture customers' opinions for the purpose of evaluating their products and services. Text mining can be useful to analyze great number of comments from ride-hailing customers in social media. Furthermore, by applying sentiment analysis, service providers can define the service categories which are good and still needing improvement. Customers' comments were taken from Twitter, and text classification method was used to classify the comments based on six predefined categories and their respective polarity. The accuracy of the classification model was 86% which was good to classify the text data. The output of this research is expected to give insight for ride-hailing service provider to understand customers' perspective about the services so that it will be easier to evaluate and improve their services based on the categories in this study.

Original languageEnglish
Title of host publicationProceedings - 2018 5th International Conference on Information Science and Control Engineering, ICISCE 2018
EditorsYun Cheng, Shaozi Li, Ying Dai
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages512-516
Number of pages5
ISBN (Electronic)9781538655009
DOIs
Publication statusPublished - 14 Jan 2019
Event5th International Conference on Information Science and Control Engineering, ICISCE 2018 - Zhengzhou, Henan, China
Duration: 20 Jul 201822 Jul 2018

Publication series

NameProceedings - 2018 5th International Conference on Information Science and Control Engineering, ICISCE 2018

Conference

Conference5th International Conference on Information Science and Control Engineering, ICISCE 2018
CountryChina
CityZhengzhou, Henan
Period20/07/1822/07/18

Keywords

  • multi-class classification
  • ride-hailing service
  • sentiment analysis
  • social media analytics
  • text mining

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