Cover Image

Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language

Social media platforms provide users with an efficient and effective way to interact with content without requiring lengthy or complex textual expressions. However, sarcasm in social media discourse has become a serious problem for researchers. Compared to English and several other main languages, t...

Full description

Saved in:
Bibliographic Details
Main Authors: Suhaimi, Suziane Haslinda, Abu Bakar, Nur Azaliah, Mohd. Azmi, Nurulhuda Firdaus
Format: Conference or Workshop Item
Language:English
Published: 2023
Subjects:
Q Science (General)
Online Access:http://eprints.utm.my/108427/1/SuzianeHaslinda2023_ConstructingandAnalysingtheMalaySarcDataset.pdf
http://eprints.utm.my/108427/
http://dx.doi.org/10.11159/cist23.126
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.108427
record_format eprints
spelling my.utm.1084272024-11-01T02:52:08Z http://eprints.utm.my/108427/ Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language Suhaimi, Suziane Haslinda Abu Bakar, Nur Azaliah Mohd. Azmi, Nurulhuda Firdaus Q Science (General) Social media platforms provide users with an efficient and effective way to interact with content without requiring lengthy or complex textual expressions. However, sarcasm in social media discourse has become a serious problem for researchers. Compared to English and several other main languages, the research on sarcasm and the accessibility of reference materials in the Malay language are still significantly lagging. Therefore, this study aims to develop a new dataset of Malay sarcasm detection by detailing each process step, from data collection to filtering to annotation. The dataset consists of two types of data: Facebook comments and its emotion reaction buttons, which include 6,325 non-sarcastic texts and 1,380 sarcastic texts. In addition, the descriptive analysis of this dataset was also conducted to determine the usage patterns of the main features of Malay sarcasm. The analysis shows that emoji is one of the features that play an essential role in determining sarcastic comments. Besides, there are pattern-based features based on the identification of high-frequency terms in the text. The resulting dataset provides diverse examples of sarcasm that consider the linguistic and cultural nuances of the language, thus improving the accuracy and reliability of identifying social media. The findings will aid future research in developing automatic Malay sarcasm detection models using machine learning. 2023 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/108427/1/SuzianeHaslinda2023_ConstructingandAnalysingtheMalaySarcDataset.pdf Suhaimi, Suziane Haslinda and Abu Bakar, Nur Azaliah and Mohd. Azmi, Nurulhuda Firdaus (2023) Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language. In: 9th World Congress on Electrical Engineering and Computer Systems and Sciences, EECSS 2023, 3 August 2023 - 5 August 2023, London, England. http://dx.doi.org/10.11159/cist23.126
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Suhaimi, Suziane Haslinda
Abu Bakar, Nur Azaliah
Mohd. Azmi, Nurulhuda Firdaus
Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language
description Social media platforms provide users with an efficient and effective way to interact with content without requiring lengthy or complex textual expressions. However, sarcasm in social media discourse has become a serious problem for researchers. Compared to English and several other main languages, the research on sarcasm and the accessibility of reference materials in the Malay language are still significantly lagging. Therefore, this study aims to develop a new dataset of Malay sarcasm detection by detailing each process step, from data collection to filtering to annotation. The dataset consists of two types of data: Facebook comments and its emotion reaction buttons, which include 6,325 non-sarcastic texts and 1,380 sarcastic texts. In addition, the descriptive analysis of this dataset was also conducted to determine the usage patterns of the main features of Malay sarcasm. The analysis shows that emoji is one of the features that play an essential role in determining sarcastic comments. Besides, there are pattern-based features based on the identification of high-frequency terms in the text. The resulting dataset provides diverse examples of sarcasm that consider the linguistic and cultural nuances of the language, thus improving the accuracy and reliability of identifying social media. The findings will aid future research in developing automatic Malay sarcasm detection models using machine learning.
format Conference or Workshop Item
author Suhaimi, Suziane Haslinda
Abu Bakar, Nur Azaliah
Mohd. Azmi, Nurulhuda Firdaus
author_facet Suhaimi, Suziane Haslinda
Abu Bakar, Nur Azaliah
Mohd. Azmi, Nurulhuda Firdaus
author_sort Suhaimi, Suziane Haslinda
title Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language
title_short Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language
title_full Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language
title_fullStr Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language
title_full_unstemmed Constructing and analysing the MalaySarc dataset: a resource for detecting and understanding sarcasm in Malay language
title_sort constructing and analysing the malaysarc dataset: a resource for detecting and understanding sarcasm in malay language
publishDate 2023
url http://eprints.utm.my/108427/1/SuzianeHaslinda2023_ConstructingandAnalysingtheMalaySarcDataset.pdf
http://eprints.utm.my/108427/
http://dx.doi.org/10.11159/cist23.126
_version_ 1814932888576065536
score 13.211869

Similar Items