Encyclopedia of Social Network Analysis and Mining

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Alhajj, Reda (Επιμελητής έκδοσης), Rokne, Jon (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2014.
• Θέματα: Computer science.; Computer communication systems.; Computers and civilization.; Bioinformatics.; System safety.; Sociophysics.; Econophysics.; Sociology.; Computer Science.; Computer Communication Networks.; Sociology, general.; Socio- and Econophysics, Population and Evolutionary Models.; Computers and Society.; Security Science and Technology.

 The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and  applications to data mining. While ESNAM  reflects the state-of-the-art in  social network research, the field  had its start in the 1930s when fundamental issues in social network research were broadly defined. These communities were limited to relatively small numbers of nodes (actors) and links. More recently the advent of electronic communication, and in particular on-line communities, have created social networks of hitherto unimaginable sizes. People around the world are directly or indirectly connected by popular social networks established using web-based platforms rather than by physical proximity. Reflecting the interdisciplinary nature of this unique field, the essential contributions of diverse disciplines, from computer science, mathematics, and statistics to sociology and behavioral science, are described among the 300 authoritative yet highly readable entries. Students will find a world of information and insight behind the familiar façade of the social networks in which they participate. Researchers and practitioners will benefit from a comprehensive perspective on the methodologies for analysis of constructed networks, and the data mining and machine learning techniques that have proved attractive for sophisticated knowledge discovery in complex applications. Also addressed is the application of social network methodologies to other domains, such as web networks and biological networks. 

 Applied Computational Geometry for Social Networks -- Basics of Social Network Model Construction and Evolution -- Current and Future Research Directions -- Data Collection, Data Extraction, and Data Preparation for Social Networks Analysis and Mining -- Data Management for Social Networks and Social Media -- Data Mining and Machine Learning Techniques for Social Networks -- Graph Theory for Social Networks (Sociograms) -- History of Social Networks: Past, Present and Future -- Internet, Web 2.0, Web Services and Semantic Web -- Linear Algebra and Statistics for Social Networks -- Online Social Networks, Social Networking Sites and Social Media -- Privacy and Security Issues in Social Networks -- Social Communities -- Social Network Analysis -- Social Network Applications in Business, Organizations, industry and Case studies -- Social Network Applications in Homeland Security, Terrorism, Fraud Detection, Public Sector, Politics and Case studies -- Social Network Applications in Scientific, Engineering, medical domain and Case studies -- Social Network Construction, Visualization and Analysis Tools -- Spatio-Temporal Aspects in Social Networks and Social Media -- Static Versus Dynamic Networks -- Technology for Online Social Networking and Human Computer Interact.