Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media
- 9h 11m
- Moussa Pourya Asl, Pantea Keikhosrokiani
- IGI Global
- 2022
Opinion mining and text analytics are used widely across numerous disciplines and fields in today’s society to provide insight into people’s thoughts, feelings, and stances. This data is incredibly valuable and can be utilized for a range of purposes. As such, an in-depth look into how opinion mining and text analytics correlate with social media and literature is necessary to better understand audiences.
The Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media introduces the use of artificial intelligence and big data analytics applied to opinion mining and text analytics on literary works and social media. It also focuses on theories, methods, and approaches in which data analysis techniques can be used to analyze data to provide a meaningful pattern. Covering a wide range of topics such as sentiment analysis and stance detection, this publication is ideal for lecturers, researchers, academicians, practitioners, and students.
About the Author
Pantea Keikhosrokiani received the Bachelor of Science degree in electrical and electronics engineering, the master’s degree in information technology from the School of Computer Sciences, Universiti Sains Malaysia (USM), Malaysia, and the Ph.D. degree in service system engineering, information system. She was a Teaching Fellow with the National Advanced IPv6 Centre of Excellence (Nav6), USM, where she is currently a Senior Lecturer with the School of Computer Sciences. Her recent book was published entitled Perspectives in the Development of Mobile Medical Information Systems: Life Cycle, Management, Methodological Approach and Application, in 2019. Her articles were published in distinguished edited books and journals, including Telematics and Informatics (Elsevier), Cognition, Technology, and Work (Springer), Taylors and Francis, and IGI Global. She was indexed by ISI, Scopus, and PubMed. Her research and teaching interests include information systems development, database systems, health and medical informatics, business intelligence, text analytics, location-based mobile applications, big data, and technopreneurship.
Moussa Pourya Asl is a Senior Lecturer in literary studies at Universiti Sains Malaysia, where he also obtained his PhD (English Literature) from School of Humanities. His primary research area is in diasporic literature and gender and cultural studies, and he has published several articles in the above-mentioned areas in Asian Ethnicity, American Studies in Scandinavia, Cogent: Arts & Humanities, Gema Online, and 3L.
In this Book
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Review on the Application of Lexicon-Based Political Sentiment Analysis in Social Media
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Text Mining and Pre-Processing Methods for Social Media Data Extraction and Processing
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A Review of Text Analytics Using Machine Learning
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Improving Comparative Opinion Mining Through Detection of Support Sentences
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Features of Semantic Similarity Assessment—Content- and Model-Based Perspectives
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A Topic Modeling-Guided Framework for Aspect-Oriented Sentiment Analysis on Social Media
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What is Love?—Text Analytics on Romance Literature from the Perspective of Authors
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Text Analytics Model to Identify the Connection Between Theme and Sentiment in Literary Works—A Case Study of Iraqi Life Writings
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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
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Opinion Mining and Text Analytics of Reader Reviews of Yoko Ogawa’s the Housekeeper and the Professor in Goodreads
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Sentiment Analysis of the Harry Potter Series Using a Lexicon-Based Approach
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Threat Emotion Analysis in Social Media—Considering Armed Conflicts as Social Extreme Events
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Depression Detection in Online Social Media Users Using Natural Language Processing Techniques
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Assessing Together the Trends in Newspaper Topics and User Opinions—A Co-Evolutionary Approach
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Sentiment Analysis and Stance Detection in Turkish Tweets About COVID-19 Vaccination
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Teleworker Experiences in #COVID-19—Insights Through Sentiment Analysis in Social Media
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Compilation of References
