Hybrid Intelligence for Social Networks

This book explains aspects of social networks, varying from development and application of new artificial intelligence and computational intelligence techniques for social networks to understanding the impact of social networks. Chapters 1 and 2 deal with the basic strategies towards social networks such as mining text from such networks and applying social network metrics using a hybrid approach; Chaps. 3 to 8 focus on the prime research areas in social networks: community detection, influence maximization and opinion mining. Chapter 9 to 13 concentrate on studying the impact and use of social networks in society, primarily in education, commerce, and crowd sourcing.

The contributions provide a multidimensional approach, and the book will serve graduate students and researchers as a reference in computer science, electronics engineering, communications, and information technology.

Contributions provide a multidimensional approach

Social Networks: Fundamentals and Applications.- MapReduce-Based K-FA Algorithm for Detecting Communities in Social Networks.- Group Search Optimization Strategy for Community Detection in Complex Networks.- Strategizing Information Dissemination in Real-Life Networks.- Nature-Inspired Heuristics Approach to Partitioning Complex Interaction Networks.- ROGO: Recommendations on the Go for Travel Tweeters.- Analysing Social Interaction Networks: Improving Teaching Learning Pedagogies.- Adapting Trustworthy Social Web Environments for the Cloud.- Enhanced Black-Hole Algorithm for Viral Marketing.- Comparative Analysis of Network Visualization Tools.- Enacting a Prioritized Health Awareness Campaign for Social Web Users.- Identifying Clusters in Complex Dynamic Social Networks Using Evolutionary Algorithms.- Using Intuitionistic Fuzzy Sets to Prioritize Relationships Among Facebook Users.- A Predictive Approach to Ranking Academic Articles.