Deep Learning-Based Implementation of Hate Speech Identification on Texts in Indonesian: Preliminary Study

Erryan Sazany, Indra Budi

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

16 Citations (Scopus)

Abstract

This paper presents an implementation of hate speech identification task for text data written in Indonesian language. There are some studies purposed for similar problem, but all of them use classical machine learning approach, whose heavily depends on the feature engineering. Switching the domain of data set means that the feature engineering should be redone. To address this issue, this preliminary research proposes another method based on deep learning approach which needs no feature engineering and is also adaptive to the varying context. Using data sets sourced from Twitter posts, the proposed method gives better result of 94.5% F1-score at a minimum.

Original languageEnglish
Title of host publicationProceedings of ICAITI 2018 - 1st International Conference on Applied Information Technology and Innovation
Subtitle of host publicationToward A New Paradigm for the Design of Assistive Technology in Smart Home Care
EditorsYance Sonatha, Rahmat Hidayat, Alde Alanda, MT Humaira, Indri Rahmayuni
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages114-117
Number of pages4
ISBN (Electronic)9781538667262
DOIs
Publication statusPublished - 10 Apr 2019
Event1st International Conference on Applied Information Technology and Innovation, ICAITI 2018 - Padang, Indonesia
Duration: 4 Sept 20185 Sept 2018

Publication series

NameProceedings of ICAITI 2018 - 1st International Conference on Applied Information Technology and Innovation: Toward A New Paradigm for the Design of Assistive Technology in Smart Home Care

Conference

Conference1st International Conference on Applied Information Technology and Innovation, ICAITI 2018
Country/TerritoryIndonesia
CityPadang
Period4/09/185/09/18

Keywords

  • abusive
  • deep learning
  • hate speech
  • machine learning
  • word embedding

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