A two-stage emotion detection on Indonesian tweets

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

8 Citations (Scopus)

Abstract

Emotion is a vital component in various Affective Computing areas such as opinion mining, sentiment analysis, e-learning applications, human-computer interaction and humor recognition. In this paper, we propose a two-stage approach for detecting emotions on Indonesian tweets. In the first stage, we extract emotion-bearing tweets from a huge number of raw tweets. In the second stage, all the extracted tweets are then classified into five well-known pre-defined emotion classes, namely love, joy, sad, fear, and anger. To do that, we devise various features (i.e., linguistic, semantic, and orthographic features) and subsequently use those proposed features to build a computational model based on machine learning approach. Our experimental results show that the proposed method is very effective. It is also worth noting that the work described in this paper is the first work on emotion analysis on Indonesian data.

Original languageEnglish
Title of host publicationICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages143-146
Number of pages4
ISBN (Electronic)9781509003624
DOIs
Publication statusPublished - 19 Feb 2016
EventInternational Conference on Advanced Computer Science and Information Systems, ICACSIS 2015 - Depok, Indonesia
Duration: 10 Oct 201511 Oct 2015

Publication series

NameICACSIS 2015 - 2015 International Conference on Advanced Computer Science and Information Systems, Proceedings

Conference

ConferenceInternational Conference on Advanced Computer Science and Information Systems, ICACSIS 2015
Country/TerritoryIndonesia
CityDepok
Period10/10/1511/10/15

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