Big Data Analytics: A Social Network Approach

Social networking has grown rapidly, creating a challenge in social network mining. This reference work covers theory, practices, and challenges in social networking, spanning disciplines like neural networking, deep learning, and artificial intelligence.

Format: Paperback / softback
Length: 316 pages
Publication date: 31 March 2021
Publisher: Taylor & Francis Ltd

Social networking has experienced a remarkable surge in recent years, leading to a staggering daily generation of data. Moreover, the diverse range of issues and intricate complexity of social networks present a significant challenge in the field of social network mining. Traditional algorithm software finds it inadequate to handle such vast and intricate datasets, necessitating the development of innovative analytic approaches and tools.

This comprehensive reference work delves into the various facets of social network analysis within the context of big data analytics. It encompasses a wide range of topics, including theory, practices, and challenges in social networking. The book spans multiple disciplines, such as neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security, and intrusion detection.

By exploring these diverse domains, the book provides a comprehensive understanding of the complex interplay between social networks and big data. It offers valuable insights and methodologies for analyzing, extracting, and interpreting valuable information from social networks, enabling researchers, practitioners, and professionals to make informed decisions and gain a deeper understanding of social dynamics and behavior.

Weight: 594g
Dimension: 234 x 156 (mm)
ISBN-13: 9780367780777