Handbook of research on opinion mining and text analytics on literary works and social media / Pantea Keikhosrokiani, and Moussa Pourya Asl, editors.

Format:

Book

Author/Creator:

Keikhosrokiani, Pantea, 1982- author.

Contributor:

Asl, Moussa Pourya, editor.

Keikhosrokiani, Pantea, editor.

Series:

Advances in web technologies and engineering (AWTE) book series.

Advances in web technologies and engineering (AWTE) book series

Language:

English

Subjects (All):

Text processing (Computer science).

Content analysis (Communication)--Data processing.

Content analysis (Communication).

Social media--Data processing.

Social media.

Physical Description:

26 PDFs (462 pages) : illustrations

Place of Publication:

Hershey PA : IGI Global, [2022]

System Details:

Mode of access: World Wide Web.

Summary:

"This book uses artificial intelligence and big data analytics to conduct opinion mining and text analytics on literary works and social media, focusing on theories, method, applications and approaches of data analytic techniques that can be used to extract and analyze data from literary books and social media, in a meaningful pattern"

Contents:

Section 1. Reviews, techniques, and approaches. Chapter 1. Review on the application of lexicon-based political sentiment analysis in social media ; Chapter 2. Text mining and pre-processing methods for social media data extraction and processing ; Chapter 3. A review of text analytics using machine learning ; Chapter 4. Improving comparative opinion mining through detection of support sentences ; Chapter 5. Features of semantic similarity assessment: content- and model-based perspectives ; Chapter 6. A topic modeling-guided framework for aspect-oriented sentiment analysis on social media

Section 2. Opinion mining and literary studies. Chapter 7. What is love?: text analytics on romance literature from the perspective of authors ; Chapter 8. Text analytics model to identify the connection between theme and sentiment in literary works: a case study of Iraqi life writings ; Chapter 9. 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 ; Chapter 10. Opinion mining and text analytics of reader reviews of Yoko Ogawa's the housekeeper and the professor in goodreads ; Chapter 11. Sentiment analysis of the Harry Potter series using a lexicon-based approach

Section 3. Opinion mining and social media. Chapter 12. Threat emotion analysis in social media: considering armed conflicts as social extreme events ; Chapter 13. Depression detection in online social media users using natural language processing techniques ; Chapter 14. Assessing together the trends in newspaper topics and user opinions: a co-evolutionary approach ; Chapter 15. Sentiment analysis and stance detection in Turkish tweets about COVID-19 vaccination ; Chapter 16. Teleworker experiences in COVID-19: insights through sentiment analysis in social media.

Notes:

Description based on print version record.

Includes bibliographical references and index.

ISBN:

1-7998-9596-3

OCLC:

1304417628