Overview
- Discusses fundamental concepts of sentiment analysis, its techniques, and its practical applications
- Explores applications of sentiment analysis in educational data mining across multiple domains
- Addresses practical considerations and challenges in implementing sentiment analysis in educational contexts
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)
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Table of contents (5 chapters)
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Front Matter
Keywords
About this book
The book delves into the fundamental concepts of sentiment analysis, its techniques, and its practical applications in the context of educational data. The book begins by introducing the concept of sentiment analysis and its relevance in educational settings. It provides a thorough overview of the various techniques used for sentiment analysis, including natural language processing, machine learning, and deep learning algorithms. The subsequent chapters explore applications of sentiment analysis in educational data mining across multiple domains. The book illustrates how sentiment analysis can be employed to analyze student feedback and sentiment patterns, enabling educators to gain valuable insights into student engagement, motivation, and satisfaction. It also examines how sentiment analysis can be used to identify and address students' emotional states, such as stress, boredom, or confusion, leading to more personalized and effective interventions. Furthermore, the book explores the integration of sentiment analysis with other educational data mining techniques, such as clustering, classification, and predictive modeling. It showcases real-world case studies and examples that demonstrate how sentiment analysis can be combined with these approaches to improve educational decision-making, curriculum design, and adaptive learning systems.
Authors and Affiliations
About the author
Dr. Soni Sweta, Ph.D. in Computer Science and Engineering from BIT, Mesra, Ranchi, is presently working as an assistant professor in the Department of Computer Science and Engineering at Mukesh Patel School of Technology, Management, and Engineering, NMIMS, Mumbai Campus, Mumbai, Maharashtra. She received her Master of Technology degree from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal. She is presently guiding many Ph.D., M.Tech, M.C.A, and B.Tech. Scholars. Previously, she had guided many M.Tech., M.C.A, B.C.A, and B.Tech. students in their dissertation and final project work. Her present areas of research are artificial intelligence, natural language processing, soft computing, data mining, machine learning, data science, etc. Being a member of IEEE and life member of CSI(India), she is associated with few reputed journals as a reviewer and member of editorial board. She has acted as a technical committee member in many reputed conferences so far.
Bibliographic Information
Book Title: Sentiment Analysis and its Application in Educational Data Mining
Authors: Soni Sweta
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-981-97-2474-1
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024
Softcover ISBN: 978-981-97-2473-4Published: 23 April 2024
eBook ISBN: 978-981-97-2474-1Published: 20 April 2024
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: XXI, 97
Number of Illustrations: 2 b/w illustrations, 6 illustrations in colour
Topics: Computational Intelligence, Data Mining and Knowledge Discovery, Natural Language Processing (NLP), Machine Learning