PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT

Anxiety and depression can have a significant impact on students’ academic performance, however, these mental health impacts were increased during the Covid-19 pandemic, and accordingly students and parents need some people to share their feelings together; however, there are different types of soci...

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Main Author: Khalil Assayed, Suha (author)
Other Authors: Shaalan, Khaled (author), Alsayed, Sana (author), Alkhatib, Manar (author)
Published: 2023
Subjects:
Online Access:https://bspace.buid.ac.ae/handle/1234/2985
https://doi.org/10.5121/ijaia.2023.14203.
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author Khalil Assayed, Suha
author2 Shaalan, Khaled
Alsayed, Sana
Alkhatib, Manar
author2_role author
author
author
author_facet Khalil Assayed, Suha
Shaalan, Khaled
Alsayed, Sana
Alkhatib, Manar
author_role author
dc.creator.none.fl_str_mv Khalil Assayed, Suha
Shaalan, Khaled
Alsayed, Sana
Alkhatib, Manar
dc.date.none.fl_str_mv 2023-03-01
2025-05-12T12:37:52Z
2025-05-12T12:37:52Z
dc.identifier.none.fl_str_mv Assayed, S.K., Shaalan, K. and Alsayed, S. (2023) “Psychological Emotion Recognition of Students using Machine Learning based Chatbot,” International Journal of Artificial Intelligence & Applications, 14(2), pp. 29–39.
0976-2191, 0976-2191
https://bspace.buid.ac.ae/handle/1234/2985
https://doi.org/10.5121/ijaia.2023.14203.
dc.language.none.fl_str_mv en_US
dc.publisher.none.fl_str_mv IJAIA
dc.relation.none.fl_str_mv International Journal of Artificial Intelligence & Applicationsv14 n2 (20230330): 29-39
dc.subject.none.fl_str_mv Psychological Emotion, NLP, Covid-19, Chatbot, Machine Learning, Students, SVM, Naïve Bayes
dc.title.none.fl_str_mv PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
dc.type.none.fl_str_mv Article
description Anxiety and depression can have a significant impact on students’ academic performance, however, these mental health impacts were increased during the Covid-19 pandemic, and accordingly students and parents need some people to share their feelings together; however, there are different types of social media apps and platforms such as Facebook, Twitter, Reddit, Instagram, and others. Twitter is one of the most popular social application that people prefer to share their emotional states. Interestingly, the psychologist and computer scientists are inspired to study these emotions. In this paper, we propose a chatbot for detecting the students feeling by using machine-learning algorithms. The authors used a dataset of tweets from Kaggle’s paltform, and it includes 41157 tweets that are all related to the COVID 19. The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. In addition to that, the classifiers were evaluated and compared after changing the test split ratio. The result shows that the accuracy performance of SVM algorithm is better than Naïve Bayes algorithm, but the speed is extremely slow compared to Naive Bayes model. In future, other neural network algorithms such as the RNN, LSTM will be implemented, and Arabic tweets will be included in the future.
id budr_9a8f2f1ba8073768a14853d7fb8b6099
identifier_str_mv Assayed, S.K., Shaalan, K. and Alsayed, S. (2023) “Psychological Emotion Recognition of Students using Machine Learning based Chatbot,” International Journal of Artificial Intelligence & Applications, 14(2), pp. 29–39.
0976-2191, 0976-2191
language_invalid_str_mv en_US
network_acronym_str budr
network_name_str The British University in Dubai repository
oai_identifier_str oai:bspace.buid.ac.ae:1234/2985
publishDate 2023
publisher.none.fl_str_mv IJAIA
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOTKhalil Assayed, SuhaShaalan, KhaledAlsayed, SanaAlkhatib, ManarPsychological Emotion, NLP, Covid-19, Chatbot, Machine Learning, Students, SVM, Naïve BayesAnxiety and depression can have a significant impact on students’ academic performance, however, these mental health impacts were increased during the Covid-19 pandemic, and accordingly students and parents need some people to share their feelings together; however, there are different types of social media apps and platforms such as Facebook, Twitter, Reddit, Instagram, and others. Twitter is one of the most popular social application that people prefer to share their emotional states. Interestingly, the psychologist and computer scientists are inspired to study these emotions. In this paper, we propose a chatbot for detecting the students feeling by using machine-learning algorithms. The authors used a dataset of tweets from Kaggle’s paltform, and it includes 41157 tweets that are all related to the COVID 19. The tweets are classified into categories based on the feeling: Positive and negative. The authors applied Machine Learning algorithms, Support Vector Machines (SVM) and the Naïve Bayes (NB) and accordingly they compared the accuracy between them. In addition to that, the classifiers were evaluated and compared after changing the test split ratio. The result shows that the accuracy performance of SVM algorithm is better than Naïve Bayes algorithm, but the speed is extremely slow compared to Naive Bayes model. In future, other neural network algorithms such as the RNN, LSTM will be implemented, and Arabic tweets will be included in the future.IJAIA2025-05-12T12:37:52Z2025-05-12T12:37:52Z2023-03-01ArticleAssayed, S.K., Shaalan, K. and Alsayed, S. (2023) “Psychological Emotion Recognition of Students using Machine Learning based Chatbot,” International Journal of Artificial Intelligence & Applications, 14(2), pp. 29–39.0976-2191, 0976-2191https://bspace.buid.ac.ae/handle/1234/2985https://doi.org/10.5121/ijaia.2023.14203.en_USInternational Journal of Artificial Intelligence & Applicationsv14 n2 (20230330): 29-39oai:bspace.buid.ac.ae:1234/29852025-08-12T17:23:43Z
spellingShingle PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
Khalil Assayed, Suha
Psychological Emotion, NLP, Covid-19, Chatbot, Machine Learning, Students, SVM, Naïve Bayes
title PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
title_full PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
title_fullStr PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
title_full_unstemmed PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
title_short PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
title_sort PSYCHOLOGICAL EMOTION RECOGNITION OF STUDENTS USING MACHINE LEARNING BASED CHATBOT
topic Psychological Emotion, NLP, Covid-19, Chatbot, Machine Learning, Students, SVM, Naïve Bayes
url https://bspace.buid.ac.ae/handle/1234/2985
https://doi.org/10.5121/ijaia.2023.14203.