An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach

Recently, the revolutionary transformations in social and political landscapes as well as the remarkable developments in artificial intelligence reinforced the importance of geography and spatial analyses in literary and cultural studies. This chapter proposes an analytical framework of topic modell...

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發表在:Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media
Main Authors: Jafery N.N., Keikhosrokiani P., Asl M.P.
格式: Book Chapter
語言:English
出版: IGI Global 2022
在線閱讀:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147981691&doi=10.4018%2f978-1-6684-6242-3.ch002&partnerID=40&md5=2bf007613a9e4c8f058fab7dd9c67e13
id 2-s2.0-85147981691
spelling 2-s2.0-85147981691
Jafery N.N., Keikhosrokiani P., Asl M.P.
An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach
2022
Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media


10.4018/978-1-6684-6242-3.ch002
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147981691&doi=10.4018%2f978-1-6684-6242-3.ch002&partnerID=40&md5=2bf007613a9e4c8f058fab7dd9c67e13
Recently, the revolutionary transformations in social and political landscapes as well as the remarkable developments in artificial intelligence reinforced the importance of geography and spatial analyses in literary and cultural studies. This chapter proposes an analytical framework of topic modelling and sentiment analysis for exploring the connection between theme, place, and sentiment in 36 autobiographical narratives by or about women from the Middle East. In the proposed framework, a latent Dirichlet allocation and latent semantic analysis algorithm from topic modelling, TextBlob library for sentiment analysis are employed to detect the place names that come together and to point out the associated themes and emotions throughout the data source. The model gives a scoring of each topical clusters and reveals that the diasporic authors are more likely to write about their hometown than their current host land. The authors hope that the merging of topic modelling and sentiment analysis would be beneficial to literary critics in the analysis of long texts. © 2023, IGI Global. All rights reserved.
IGI Global

English
Book Chapter

author Jafery N.N.
Keikhosrokiani P.
Asl M.P.
spellingShingle Jafery N.N.
Keikhosrokiani P.
Asl M.P.
An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach
author_facet Jafery N.N.
Keikhosrokiani P.
Asl M.P.
author_sort Jafery N.N.
title An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach
title_short An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach
title_full An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach
title_fullStr An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach
title_full_unstemmed An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach
title_sort An artificial intelligence application of theme and space in life writings of middle eastern women: A topic modelling and sentiment analysis approach
publishDate 2022
container_title Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media
container_volume
container_issue
doi_str_mv 10.4018/978-1-6684-6242-3.ch002
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147981691&doi=10.4018%2f978-1-6684-6242-3.ch002&partnerID=40&md5=2bf007613a9e4c8f058fab7dd9c67e13
description Recently, the revolutionary transformations in social and political landscapes as well as the remarkable developments in artificial intelligence reinforced the importance of geography and spatial analyses in literary and cultural studies. This chapter proposes an analytical framework of topic modelling and sentiment analysis for exploring the connection between theme, place, and sentiment in 36 autobiographical narratives by or about women from the Middle East. In the proposed framework, a latent Dirichlet allocation and latent semantic analysis algorithm from topic modelling, TextBlob library for sentiment analysis are employed to detect the place names that come together and to point out the associated themes and emotions throughout the data source. The model gives a scoring of each topical clusters and reveals that the diasporic authors are more likely to write about their hometown than their current host land. The authors hope that the merging of topic modelling and sentiment analysis would be beneficial to literary critics in the analysis of long texts. © 2023, IGI Global. All rights reserved.
publisher IGI Global
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language English
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