Emotion Classification on Indonesian Twitter Dataset

Mei Silviana Saputri, Rahmad Mahendra, Mirna Adriani

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

4 Citations (Scopus)

Abstract

The rapid growth of Twitter usage attracts many researchers to utilize Twitter data for several purposes, including emotion analysis. However, there is a resource limitation in standard dataset for emotion analysis task for under-resourced language, especially Indonesian. In this study, we build an Indonesian twitter dataset for emotion classification task which is publicly available. In addition, we conduct feature engineering to decide the best feature in emotion classification. The features used in this research are lexicon-based, Bag-of-Words, word embeddings, orthography and Part-Of-Speech (POS)tag features. We test those features in two datasets with different characteristics. F1-score is employed as an evaluation metric. The results of our experiments show that implementing the combination of all proposed features in our built dataset can achieve 69.73% of F1-Score, which outperforms the baseline model by 26.64%.

Original languageEnglish
Title of host publicationProceedings of the 2018 International Conference on Asian Language Processing, IALP 2018
EditorsMinghui Dong, Fariska Z. Ruskanda, Herry Sujaini, Ade Romadhony, Moch. Bijaksana, Elvira Nurfadhilah, Lyla Ruslana Aini, Arif Bijaksana Putra Negara
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages90-95
Number of pages6
ISBN (Electronic)9781728111766
DOIs
Publication statusPublished - 28 Jan 2019
Event22nd International Conference on Asian Language Processing, IALP 2018 - Bandung, Indonesia
Duration: 15 Nov 201817 Nov 2018

Publication series

NameProceedings of the 2018 International Conference on Asian Language Processing, IALP 2018

Conference

Conference22nd International Conference on Asian Language Processing, IALP 2018
Country/TerritoryIndonesia
CityBandung
Period15/11/1817/11/18

Keywords

  • emotion classification
  • feature engineering
  • indonesian tweet
  • natural language processing

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