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State of the Art Applications of Social Network Analysis

Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine le...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Can, Fazli (Editor ), Özyer, Tansel (Editor ), Polat, Faruk (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:Lecture Notes in Social Networks,
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • A Randomized Approach for Structural and Message based Private Friend Recommendation in Online Social Networks
  • Context Based Semantic Relations in Tweets
  • Fast exact and approximate computation of betweenness centrality in social networks
  • Network Simulation
  • Early Stage Conversation Catalysts on Entertainment-Based Web Forums
  • Predicting Users Behaviours in Distributed Social Networks Using Community Analysis
  • What should we protect? Defining differential privacy for social network analysis
  • Complex Network Analysis of Research Funding: A Case Study of NSF Grants
  • Community Evolutionary Events in Online Social Networks
  • @Rank: Personalized Centrality Measure for Email Communication Networks
  • Twitter Sentiment Analysis: How To Hedge Your Bets In The Stock Markets
  • The Impact of Measurement Time on Subgroup Detection in Online Communities
  • Spatial and Temporal Evaluation of Network-Based Analysis of Human Mobility
  • An Ant based Particle Swarm Optimization Algorithm for Maximum Clique Problem in Social networks
  • XEngine: An XML Search Engine for Social Groups
  • Size, diversity and components in the network around an entrepreneur: Shaped by culture and shaping embeddedness of firm relations
  • Content Mining of Microblogs.