Detecting sarcasm in Bengali comments using NLP

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Bibliographic Details
Main Author:	Chowdhury, Md. Jamiur Rahman
Other Authors:	Shakil, Mr. Arif
Format:	Thesis
Language:	English
Published:	Brac University 2024
Subjects:	Natural language processing Sentiment analysis Machine learning Support vector machines Word2vec Bert Computational linguistics. Natural language processing (Computer science)
Online Access:	http://hdl.handle.net/10361/22082

id	10361-22082
record_format	dspace
spelling	10361-220822024-01-09T21:02:58Z Detecting sarcasm in Bengali comments using NLP Chowdhury, Md. Jamiur Rahman Shakil, Mr. Arif Department of Computer Science and Engineering, Brac University Natural language processing Sentiment analysis Machine learning Support vector machines Word2vec Bert Computational linguistics. Natural language processing (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 31-33). Natural Language Processing (NLP) is a subset of Machine Learning which resides at the intersection of Linguistics and Computer Science. It deals with the capability of computers to learn and work with human languages. With the emergence of social media platforms, modern-day communication is being digitalized more than ever. To keep up with this rapid flow of development, the advancement of automated text processing and artificial language interpretation has become necessary. These concerns have given birth to a domain called Sentiment Analysis where blocks of text are processed to extract prominent sentiments that are prevalent within them. These sentiments can be happiness, sadness, anger, disgust, etc. Over the past few years, similar studies have garnered the attention of a vast number of computer scientists and linguists but as the study progresses and expands in the form of lan guages, concentrations, and contexts more and more challenges have started to show up. One of these challenges is the interpretation of figurative language. Figurative language refers to the structure of speech where the actual meaning defers from the literal meaning. The best example of this is Sarcasm which is a sort of figu rative language used with an intention of mockery or humor. Detecting sarcasm is considered to be one of the most challenging tasks in the domain of NLP due to the figurative structure and creative nature of sarcastic texts and the lack of relevant data on the internet. Determining sarcasm can often be difficult for even human beings as one has to have a strong understanding of the context to detect sarcasm. However, many studies have achieved respectable results by following the context unaware unimodal methods using classical Machine Learning, Deep and Hy brid Neural Networks. Motivated by such research, the objective of this paper is to take a step toward detecting sarcasm in the Bengali Language domain using Sup port Vector Machine (SVM), Cogniinsight(Word2Vec), and Bidirectional Encoder Representations from Transformers (BERT) on a novel dataset. To the best of my knowledge, this will be the first-ever initiative taken toward detecting sarcasm in Bengali Language using BERT. Md. Jamiur Rahman Chowdhury B.Sc. in Computer Science and Engineering 2024-01-09T05:26:55Z 2024-01-09T05:26:55Z 2023 2023-01 Thesis ID: 18101448 http://hdl.handle.net/10361/22082 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 33 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Natural language processing Sentiment analysis Machine learning Support vector machines Word2vec Bert Computational linguistics. Natural language processing (Computer science)
spellingShingle	Natural language processing Sentiment analysis Machine learning Support vector machines Word2vec Bert Computational linguistics. Natural language processing (Computer science) Chowdhury, Md. Jamiur Rahman Detecting sarcasm in Bengali comments using NLP
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
author2	Shakil, Mr. Arif
author_facet	Shakil, Mr. Arif Chowdhury, Md. Jamiur Rahman
format	Thesis
author	Chowdhury, Md. Jamiur Rahman
author_sort	Chowdhury, Md. Jamiur Rahman
title	Detecting sarcasm in Bengali comments using NLP
title_short	Detecting sarcasm in Bengali comments using NLP
title_full	Detecting sarcasm in Bengali comments using NLP
title_fullStr	Detecting sarcasm in Bengali comments using NLP
title_full_unstemmed	Detecting sarcasm in Bengali comments using NLP
title_sort	detecting sarcasm in bengali comments using nlp
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/22082
work_keys_str_mv	AT chowdhurymdjamiurrahman detectingsarcasminbengalicommentsusingnlp
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Detecting sarcasm in Bengali comments using NLP

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