Indonesian Finance News Sentiment from Hybrid Deep Learning and Support Vector Machine

Imam Mukhlash, Athyah D.S. Gama, Mohammad Iqbal*, Darmaji Darmaji, Masaomi Kimura

*Corresponding author for this work

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

Abstract

One common action to keep aware of the current investment progress is by updating finance news continuously. Indeed, we can read a bunch of news relating to finance from social media, which is often difficult to figure out at a glance. Hence, this work aims to propose hybrid models that can help us to classify whether the finance news is positive to follow. Also, we may sort a few articles containing neutral ones. More specifically, we incorporate deep neural networks: deep convolutional neural networks and long short term memory, to draw diverse word representations, and support vector machines to categorize them as a multi-class classification case. In this work, we evaluated the proposed models on Indonesian finance news that was officially reported from the Bank of Indonesia around 2019 before the pandemic started. In the evaluation results, we showed the DCNN-SVM better accuracy compared to others.

Original languageEnglish
Title of host publicationICoMS 2022 - Proceedings of 2022 5th International Conference on Mathematics and Statistics
PublisherAssociation for Computing Machinery
Pages115-119
Number of pages5
ISBN (Electronic)9781450396233
DOIs
Publication statusPublished - 17 Jun 2022
Event5th International Conference on Mathematics and Statistics, ICoMS 2022 - Paris, France
Duration: 17 Jun 202219 Jun 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Conference on Mathematics and Statistics, ICoMS 2022
Country/TerritoryFrance
CityParis
Period17/06/2219/06/22

Keywords

  • Deep Learning
  • Finance News
  • SVM
  • Text Classification

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