Social Network Analysis and Mining Applications in Healthcare and Anomaly Detection (Lecture Notes in Social Networks)

By: Mehmet Kaya and Sleiman Alhajj and Kashfia Sailunaz and Min-Yuh Day

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Synopsis: This book is an excellent source of knowledge for readers interested in the latest developments in social network analysis and mining, particularly with applications in healthcare and anomaly detection. It covers topics such as sensitivity to noise in features, enhancing fraud detection in financial systems, measuring the echo-chamber phenomenon, detecting comorbidity, and evaluating the effectiveness of mitigative and preventative actions on viral spread in small communities using agent-based stochastic simulations. Additionally, it discusses predicting behavior, measuring and identifying influence, analyzing the impact of COVID-19 on various social aspects, and using UNet for handling various skin conditions. This book helps readers develop their own perspectives on adapting social network concepts to various applications. It also demonstrates how to use various machine learning techniques for tackling challenges in social network analysis and mining.

Book Quality:: Publisher Quality
ISBN-13:: 9783031752049
Related ISBNs:: 9783031752032
Publisher:: Springer Nature Switzerland
Date of Addition:: 01/21/25
Copyrighted By:: The Editor
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Computers and Internet, Social Studies, Mathematics and Statistics, Medicine
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: Mehmet Kaya
Edited by:: Sleiman Alhajj
Edited by:: Kashfia Sailunaz
Edited by:: Min-Yuh Day