Big Data Analytics A Social Network Approach
Big Data Analytics A Social Network Approach by Mrutyunjaya Panda, published by Taylor & Francis Group on March 31, 2021, is a comprehensive exploration of the intersection between social networking and big data analytics. This 316-page book addresses the challenges posed by the increasing volume and complexity of data generated through social networks, highlighting the limitations of traditional algorithm software in managing such vast datasets.
Readers will find a detailed examination of various aspects of social network analytics, including theoretical frameworks, practical applications, and the challenges faced in this rapidly evolving field. The book spans multiple disciplines, incorporating topics such as neural networking, deep learning, and artificial intelligence, while also discussing visualization techniques and their relevance in areas like e-learning and e-healthcare. This edition serves as a valuable resource for those interested in the fields of data science, statistics, and computer science, providing insights into innovative analytic approaches and tools necessary for effective social network mining.
Official synopsis Publisher
Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools.
This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.
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