Reference Hub

This research has been cited in:

Article
Decoding violence against women: analysing harassment in middle eastern literature with machine learning and sentiment analysisHumanities and Social Sciences Communications10.1057/s41599-024-02908-7
Chapter
Kevin Kwan’s Crazy Rich Asians: Opinion Mining and Emotion Detection on Fans’ Comments on Social MediaAdvances on Intelligent Computing and Data Science10.1007/978-3-031-36258-3_2
Chapter
Opinion Mining on Paul W. S. Anderson’s Monster Hunter from Chinese Social Media Using Sentiment AnalysisAdvances on Intelligent Computing and Data Science10.1007/978-3-031-36258-3_1
Article
A Topic Modeling and Sentiment Analysis Model for Detection and Visualization of Themes in Literary TextsPertanika Journal of Science and Technology10.47836/pjst.30.4.14
Chapter
Drug Recommendation System for Healthcare Professionals’ Decision-Making Using Opinion Mining and Machine LearningDigital Health and Wireless Solutions10.1007/978-3-031-59091-7_15
Chapter
Artificial Intelligence Framework for Opinion Mining of Netizen Readers' Reviews of Arundhati Roy's The God of Small ThingsHandbook of Research on Artificial Intelligence Applications in Literary Works and Social Media10.4018/978-1-6684-6242-3.ch004
Chapter
An Artificial Intelligence Application of Theme and Space in Life Writings of Middle Eastern WomenHandbook of Research on Artificial Intelligence Applications in Literary Works and Social Media10.4018/978-1-6684-6242-3.ch002
Chapter
A Review on Virtual Reality and EduverseHandbook of Research on Consumer Behavioral Analytics in Metaverse and the Adoption of a Virtual World10.4018/978-1-6684-7029-9.ch005
Chapter
Artificial Intelligence Applications in Literary WorksHandbook of Research on Artificial Intelligence Applications in Literary Works and Social Media10.4018/978-1-6684-6242-3.ch005
Chapter
Narrative Threads and Cinematic Connections Using Intelligent Systems to Enhance Movie Recommendations with Market Basket Analysis and Advanced AlgorithmsData-Driven Business Intelligence Systems for Socio-Technical Organizations10.4018/979-8-3693-1210-0.ch013
Chapter
Sentiment Analysis of User Reactions to Meta's Threads Launch and Twitter's X RenamingData-Driven Business Intelligence Systems for Socio-Technical Organizations10.4018/979-8-3693-1210-0.ch015
Chapter
Synergizing SuccessData-Driven Business Intelligence Systems for Socio-Technical Organizations10.4018/979-8-3693-1210-0.ch005
Chapter
Artificial Intelligence and Human Rights ActivismHandbook of Research on Artificial Intelligence Applications in Literary Works and Social Media10.4018/978-1-6684-6242-3.ch006
Chapter
The Critical Success Factors of Metaverse Adoption in EducationHandbook of Research on Consumer Behavioral Analytics in Metaverse and the Adoption of a Virtual World10.4018/978-1-6684-7029-9.ch009
Chapter
A Machine Learning Approach to the Analytics of Representations of Violence in Khaled Hosseini's NovelsHandbook of Research on Artificial Intelligence Applications in Literary Works and Social Media10.4018/978-1-6684-6242-3.ch003
Chapter
Introduction to Artificial Intelligence for the Analytics of Literary Works and Social MediaHandbook of Research on Artificial Intelligence Applications in Literary Works and Social Media10.4018/978-1-6684-6242-3.ch001
Chapter
A Concise Review on the Concept of MetaverseHandbook of Research on Consumer Behavioral Analytics in Metaverse and the Adoption of a Virtual World10.4018/978-1-6684-7029-9.ch003
Chapter
Analytics of Public Reactions to the COVID-19 Vaccine on Twitter Using Sentiment Analysis and Topic ModellingHandbook of Research on Applied Artificial Intelligence and Robotics for Government Processes10.4018/978-1-6684-5624-8.ch008
Chapter
Virtual World and the Teaching of Literature Studies in IR 4.0 EraHandbook of Research on Consumer Behavioral Analytics in Metaverse and the Adoption of a Virtual World10.4018/978-1-6684-7029-9.ch013

Opinion Mining and Text Analytics of Literary Reader Responses: A Case Study of Reader Responses to KL Noir Volumes in Goodreads Using Sentiment Analysis and Topic

Nikmatul Husna Binti Suhendra, Pantea Keikhosrokiani, Moussa Pourya Asl, Xian Zhao

Source Title: Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media

ISBN13: 9781799895947|ISBN10: 1799895947|ISBN13 Softcover: 9781799895954|EISBN13: 9781799895961

DOI: 10.4018/978-1-7998-9594-7.ch009

Cite Chapter Cite Chapter

MLA

Suhendra, Nikmatul Husna Binti, et al. "Opinion Mining and Text Analytics of Literary Reader Responses: A Case Study of Reader Responses to KL Noir Volumes in Goodreads Using Sentiment Analysis and Topic." Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media, edited by Pantea Keikhosrokiani and Moussa Pourya Asl, IGI Global, 2022, pp. 191-239. https://doi.org/10.4018/978-1-7998-9594-7.ch009

APA

Suhendra, N. H., Keikhosrokiani, P., Asl, M. P., & Zhao, X. (2022). Opinion Mining and Text Analytics of Literary Reader Responses: A Case Study of Reader Responses to KL Noir Volumes in Goodreads Using Sentiment Analysis and Topic. In P. Keikhosrokiani & M. Pourya Asl (Eds.), Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media (pp. 191-239). IGI Global. https://doi.org/10.4018/978-1-7998-9594-7.ch009

Chicago

Suhendra, Nikmatul Husna Binti, et al. "Opinion Mining and Text Analytics of Literary Reader Responses: A Case Study of Reader Responses to KL Noir Volumes in Goodreads Using Sentiment Analysis and Topic." In Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media, edited by Pantea Keikhosrokiani and Moussa Pourya Asl, 191-239. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-7998-9594-7.ch009

Export Reference

Favorite

View Full Text HTML

View Full Text PDF

Abstract

Text mining is an important field of study that has proved beneficial for scholars of various disciplines. Literary scholars use text mining to examine the data produced by creative writers, literary readers, publishers, and distributing companies. The produced data are generally in unstructured form that cannot be used to extract useful information. Text mining can discover the unstructured data and convert it to interesting information through several processes. This chapter proposes a text mining technique by using topic modelling and sentiment analysis to retrieve information about the attitude of the user-readers toward the four volumes of KL Noir books on the Goodreads website. The main significance of this approach is to gain the trends by analyzing the book reviews written on Goodreads.

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.

Username or email: *

Password: *

Forgot individual login password?

Create individual account

Opinion Mining and Text Analytics of Literary Reader Responses: A Case Study of Reader Responses to KL Noir Volumes in Goodreads Using Sentiment Analysis and Topic

MLA

APA

Chicago

Export Reference

Abstract

Request Access