Aspect Category Detection on Indonesian E-commerce Mobile Application Review

Denanir F. Nasiri, Indra Budi

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

Abstract

E-commerce platform has a great influence on the growth of digital economy in Indonesia. This promising sector creates a fierce competition between e-commerce platforms. User reviews can be utilized to discover useful information for both developers and users. Developers use them for enhancing their application, while users take them as a consideration for using the application. We perform aspect category detection to retrieve the important aspects in reviews. We gather and analyze any aspect categories related to e-commerce and find that new potential aspects can be obtained from mobile application reviews, such as promos and payment. For identifying the aspects, we employ two different approaches, one-vs-all and single model, for 3748 annotated reviews. In one-vs-all we compare Naive Bayes, SVM, and the effect on using class-weights in SVM, since the distribution in the dataset is imbalanced. Meanwhile, we implement neural networks architecture for single model. We compare CNN to GRU+CNN architecture. GRU+CNN successfully achieves overall best result on both example-based and label-based performance metrics for multi-label task in our dataset. In example-based we use Hamming score to calculate the accuracy where GRU+CNN gets 71%, and it obtains 78% samples average F1-score for labelbased metric.

Original languageEnglish
Title of host publicationProceedings of 2019 International Conference on Data and Software Engineering, ICoDSE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728149929
DOIs
Publication statusPublished - Nov 2019
Event2019 International Conference on Data and Software Engineering, ICoDSE 2019 - Pontianak, Indonesia
Duration: 13 Nov 201914 Nov 2019

Publication series

NameProceedings of 2019 International Conference on Data and Software Engineering, ICoDSE 2019

Conference

Conference2019 International Conference on Data and Software Engineering, ICoDSE 2019
Country/TerritoryIndonesia
CityPontianak
Period13/11/1914/11/19

Keywords

  • application review
  • aspect detection
  • e-commerce
  • Indonesian review
  • multi-label

Fingerprint

Dive into the research topics of 'Aspect Category Detection on Indonesian E-commerce Mobile Application Review'. Together they form a unique fingerprint.

Cite this