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...
發表在: | Handbook of Research on Artificial Intelligence Applications in Literary Works and Social Media |
---|---|
Main Authors: | , , |
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 |
issn |
|
language |
English |
format |
Book Chapter |
accesstype |
|
record_format |
scopus |
collection |
Scopus |
_version_ |
1791586716798156800 |