Investigating the challenges of sarcasm prediction

This project delves deep into the intricate nature of sarcasm detection in Natural Language Processing (NLP). Sarcasm, being a complex linguistic construct, often relies on contextual cues and incongruities, making its automatic detection particularly challenging in textual data. This research aims...

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Main Author:	Chua, Rachel Jing Wen
Other Authors:	Wang Wenya
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2024
Subjects:	Computer and Information Science
Online Access:	https://hdl.handle.net/10356/181034
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-1810342024-11-12T02:27:41Z Investigating the challenges of sarcasm prediction Chua, Rachel Jing Wen Wang Wenya College of Computing and Data Science wangwy@ntu.edu.sg Computer and Information Science This project delves deep into the intricate nature of sarcasm detection in Natural Language Processing (NLP). Sarcasm, being a complex linguistic construct, often relies on contextual cues and incongruities, making its automatic detection particularly challenging in textual data. This research aims to identify and dissect the multifaceted challenges posed by sarcasm in computational models. The study will analyse the performance of DL models in sarcasm prediction, examine the role of context, the effect of additional knowledge, and possibly explore potential strategies to overcome identified challenges. Bachelor's degree 2024-11-12T02:27:41Z 2024-11-12T02:27:41Z 2024 Final Year Project (FYP) Chua, R. J. W. (2024). Investigating the challenges of sarcasm prediction. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/181034 https://hdl.handle.net/10356/181034 en SCSE23-1049 application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Computer and Information Science
spellingShingle	Computer and Information Science Chua, Rachel Jing Wen Investigating the challenges of sarcasm prediction
description	This project delves deep into the intricate nature of sarcasm detection in Natural Language Processing (NLP). Sarcasm, being a complex linguistic construct, often relies on contextual cues and incongruities, making its automatic detection particularly challenging in textual data. This research aims to identify and dissect the multifaceted challenges posed by sarcasm in computational models. The study will analyse the performance of DL models in sarcasm prediction, examine the role of context, the effect of additional knowledge, and possibly explore potential strategies to overcome identified challenges.
author2	Wang Wenya
author_facet	Wang Wenya Chua, Rachel Jing Wen
format	Final Year Project
author	Chua, Rachel Jing Wen
author_sort	Chua, Rachel Jing Wen
title	Investigating the challenges of sarcasm prediction
title_short	Investigating the challenges of sarcasm prediction
title_full	Investigating the challenges of sarcasm prediction
title_fullStr	Investigating the challenges of sarcasm prediction
title_full_unstemmed	Investigating the challenges of sarcasm prediction
title_sort	investigating the challenges of sarcasm prediction
publisher	Nanyang Technological University
publishDate	2024
url	https://hdl.handle.net/10356/181034
_version_	1816858959214018560

Investigating the challenges of sarcasm prediction

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