Big Data Analytics: A Social Network Approach

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.

Mrutyunjaya Panda is a Reader in the Department of Computer Science and Application, Utkal University, Bhubaneswar, Odisha, India. His areas of research include Data Mining, Intrusion Detection, Mobile Communication, Social Networking, Sensor Network and Image Processing.

Aboul-Ella Hassanien (Abo) is a Professor in the Faculty of Computers and Information, IT Department, Cairo University, and the Chair of the Technology Center of Blind and Visually Impaired People.

Ajith Abraham is the Director of Machine Intelligence Research Labs (MIR Labs), USA which has more than 1,000 scientific members from over 100 countries. He works in a multi-disciplinary environment involving Machine Intelligence, Cyber-physical Systems, Internet of Things, Network Security, Sensor Networks, Web Intelligence and its applications in various real-world problems.