What Users Want for Gig Economy Platforms: Sentiment Analysis Approach

Nadina Adelia Indrawan, Yudho Giri Sucahyo, Yova Ruldeviyani, Arfive Gandhi

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

Abstract

Gig economy-based mobile applications are increasingly in demand by the public. An increment in the number of users rises the number of downloads and reviews. However, the number of reviews makes it difficult for developers to understand the information contained in reviews. Besides, one review can have a variety of information. This study proposes a model that can categorize content and sentiment reviews using Support Vector Machine (SVM), Multinomial Naïve Bayes, Complement Naïve Bayes classifier, and Binary Relevance, Classifier Chain, and Label Power Sets as the data transformation method. This study used the reviews contained in the Gojek, Sampingan, and Ruang Guru applications, with 10, 123 reviews. This study found the review text's length influenced accuracy based on the evaluation of Gojek application. Generally, this study results showed that the SVM algorithm (both in the classification of sentiment reviews and review categorization) and Label Power Sets as the transformation method, yielded the best accuracy.

Original languageEnglish
Title of host publication2020 6th International Conference on Science in Information Technology
Subtitle of host publicationEmbracing Industry 4.0: Towards Innovation in Disaster Management, ICSITech 2020
EditorsAnita Ahmad Kasim, Andri Pranolo, Leonel Hernandez, Aji Prasetya Wibawa, Roman Voliansky, Hajra Rasmita Ngemba, Rafal Drezewski, Zachir Zachir, Haviluddin Haviluddin
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages68-73
Number of pages6
ISBN (Electronic)9781728173498
DOIs
Publication statusPublished - 21 Oct 2020
Event6th International Conference on Science in Information Technology, ICSITech 2020 - Palu, Indonesia
Duration: 21 Oct 202022 Oct 2020

Publication series

Name2020 6th International Conference on Science in Information Technology: Embracing Industry 4.0: Towards Innovation in Disaster Management, ICSITech 2020

Conference

Conference6th International Conference on Science in Information Technology, ICSITech 2020
CountryIndonesia
CityPalu
Period21/10/2022/10/20

Keywords

  • classification
  • machine learning
  • multi-label
  • sentiment analysis
  • user reviews

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