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Dwi A. P. Rahayu
University of Muhammadiyah Malang
Computer Science & IT Electrical & Electronics Engineering

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Sarcasm Detection on Indonesian Twitter Feeds Dwi A. P. Rahayu; Soveatin Kuntur; Nur Hayatin
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 5: EECSI 2018
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (393.127 KB) | DOI: 10.11591/eecsi.v5.1724

Abstract

In social media, some people use positive words to express negative opinion on a topic which is known as sarcasm. The existence of sarcasm becomes special because it is hard to be detected using simple sentiment analysis technique. Research on sarcasm detection in Indonesia is still very limited. Therefore, this research proposes a technique in detecting sarcasm in Indonesian Twitter feeds particularly on several critical issues such as politics, public figure and tourism. Our proposed technique uses two feature extraction methods namely interjection and punctuation. These methods are later used in two different weighting and classification algorithms. The empirical results demonstrate that combination of feature extraction methods, tf-idf, k-Nearest Neighbor yields the best performance in detecting sarcasm.
Co-Authors Nur Hayatin Soveatin Kuntur