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Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications

With the widespread usage of social media in our day-to-day lives, it becomes a platform for persons to express and share their feelings, views, thoughts, and opinions. Recognizing emotions has numerous applications extending from dynamic advertisement to behavior analyses. People express their emot...

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Main Authors: Mahzari, Mohammad, Hassan Abdalla Hashim, Aisha, Saeed, Khalid M. Osman, Mokhtar, Mohammed M. Osman
Format: Article
Language:English
English
Published: American Scientific Publishing Group (ASPG) 2024
Subjects:
TK7885 Computer engineering
Online Access:http://irep.iium.edu.my/114649/7/114649_Two-person%20intuitionistic%20neutrosophic%20soft%20games_SCOPUS.pdf
http://irep.iium.edu.my/114649/8/114649_Two-person%20intuitionistic%20neutrosophic%20soft%20games.pdf
http://irep.iium.edu.my/114649/
https://www.americaspg.com/articleinfo/21/show/2782
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spelling my.iium.irep.1146492024-09-25T02:56:22Z http://irep.iium.edu.my/114649/ Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications Mahzari, Mohammad Hassan Abdalla Hashim, Aisha Saeed, Khalid M. Osman Mokhtar, Mohammed M. Osman TK7885 Computer engineering With the widespread usage of social media in our day-to-day lives, it becomes a platform for persons to express and share their feelings, views, thoughts, and opinions. Recognizing emotions has numerous applications extending from dynamic advertisement to behavior analyses. People express their emotional state in a language that is often complemented by figures of speech and ambiguity, making it problematic even for human beings to understand. Categorizing tweets is a dynamic application of NLP, allowing the scrutiny of topical discussions, user opinions, and trends in real-time. Leveraging techniques such as word embeddings, machine learning, and text preprocessing approaches, tweet classification enables tasks like spam detection, sentiment analysis, and topic modeling. This ability assists companies in understanding client feedback and allows policymakers and researchers to track emerging issues and gauge public opinion on social networking media. This study presents a Two-Person Intuitionistic Neutrosophic Soft Games with Harris Hawks Optimizer (TINSG-HHO) based Tweets Classification on NLP Applications. The purpose of the TINSG-HHO technique is to detect the existence of different kinds of emotions or sentiments in the tweets. The TINSG-HHO technique begins with preprocessing of tweets to convert them into useful format. Then, FastText embedding represents words as contextual similarities, dense vectors, and capturing semantic nuances. Leveraging the embedding, the Neutrosophic classification model proficiently handles vagueness and uncertainty intrinsic in deceptive content detection tasks. Moreover, the HHO technique enhances the parameter of the Neutrosophic classifier, improving its generalization capabilities and performance. Based on the hunting strategy of Harris's hawks, HHO discovers the parameter range to search for optimum configurations for the classifier. Experimental evaluations carried out on different datasets illustrate the effectiveness of the DCRM in precisely detecting the deceptive content American Scientific Publishing Group (ASPG) 2024-04 Article PeerReviewed application/pdf en http://irep.iium.edu.my/114649/7/114649_Two-person%20intuitionistic%20neutrosophic%20soft%20games_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/114649/8/114649_Two-person%20intuitionistic%20neutrosophic%20soft%20games.pdf Mahzari, Mohammad and Hassan Abdalla Hashim, Aisha and Saeed, Khalid M. Osman and Mokhtar, Mohammed M. Osman (2024) Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications. International Journal of Neutrosophic Science, 24 (1). pp. 314-326. ISSN 2692-6148 E-ISSN 2690-6805 https://www.americaspg.com/articleinfo/21/show/2782 doi:10.54216/IJNS.240128
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic TK7885 Computer engineering
spellingShingle TK7885 Computer engineering
Mahzari, Mohammad
Hassan Abdalla Hashim, Aisha
Saeed, Khalid M. Osman
Mokhtar, Mohammed M. Osman
Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications
description With the widespread usage of social media in our day-to-day lives, it becomes a platform for persons to express and share their feelings, views, thoughts, and opinions. Recognizing emotions has numerous applications extending from dynamic advertisement to behavior analyses. People express their emotional state in a language that is often complemented by figures of speech and ambiguity, making it problematic even for human beings to understand. Categorizing tweets is a dynamic application of NLP, allowing the scrutiny of topical discussions, user opinions, and trends in real-time. Leveraging techniques such as word embeddings, machine learning, and text preprocessing approaches, tweet classification enables tasks like spam detection, sentiment analysis, and topic modeling. This ability assists companies in understanding client feedback and allows policymakers and researchers to track emerging issues and gauge public opinion on social networking media. This study presents a Two-Person Intuitionistic Neutrosophic Soft Games with Harris Hawks Optimizer (TINSG-HHO) based Tweets Classification on NLP Applications. The purpose of the TINSG-HHO technique is to detect the existence of different kinds of emotions or sentiments in the tweets. The TINSG-HHO technique begins with preprocessing of tweets to convert them into useful format. Then, FastText embedding represents words as contextual similarities, dense vectors, and capturing semantic nuances. Leveraging the embedding, the Neutrosophic classification model proficiently handles vagueness and uncertainty intrinsic in deceptive content detection tasks. Moreover, the HHO technique enhances the parameter of the Neutrosophic classifier, improving its generalization capabilities and performance. Based on the hunting strategy of Harris's hawks, HHO discovers the parameter range to search for optimum configurations for the classifier. Experimental evaluations carried out on different datasets illustrate the effectiveness of the DCRM in precisely detecting the deceptive content
format Article
author Mahzari, Mohammad
Hassan Abdalla Hashim, Aisha
Saeed, Khalid M. Osman
Mokhtar, Mohammed M. Osman
author_facet Mahzari, Mohammad
Hassan Abdalla Hashim, Aisha
Saeed, Khalid M. Osman
Mokhtar, Mohammed M. Osman
author_sort Mahzari, Mohammad
title Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications
title_short Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications
title_full Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications
title_fullStr Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications
title_full_unstemmed Two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on NLP applications
title_sort two-person intuitionistic neutrosophic soft games with harris hawks optimizer based tweets classification on nlp applications
publisher American Scientific Publishing Group (ASPG)
publishDate 2024
url http://irep.iium.edu.my/114649/7/114649_Two-person%20intuitionistic%20neutrosophic%20soft%20games_SCOPUS.pdf
http://irep.iium.edu.my/114649/8/114649_Two-person%20intuitionistic%20neutrosophic%20soft%20games.pdf
http://irep.iium.edu.my/114649/
https://www.americaspg.com/articleinfo/21/show/2782
_version_ 1811679662901821440
score 13.211869

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