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Encyclopedia of Social Network Analysis and Mining

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Encyclopedia of Social Network Analysis and Mining/ edited by Reda Alhajj, Jon Rokne.
其他作者:	Alhajj, Reda.
面頁冊數:	847 illus., 614 illus. in color. eReference.online resource. :
Contained By:	Springer Nature eReference
標題:	Data mining. -
電子資源:	https://doi.org/10.1007/978-1-4939-7131-2
ISBN:	9781493971312

Encyclopedia of Social Network Analysis and Mining
Encyclopedia of Social Network Analysis and Mining[electronic resource] /edited by Reda Alhajj, Jon Rokne. - 2nd ed. 2018. - 847 illus., 614 illus. in color. eReference.online resource.

Applied Computational Geometry for Social Networks -- Basics of Social Network Model Construction and Evolution -- Crowdsourcing, Opinion Mining, Fusion and Influence Analysis -- 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 -- Sentiment Analysis and Recommender Systems -- 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 Interaction.

Social Network Analysis and Mining Encyclopedia (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. The second edition of ESNAM is a truly outstanding reference appealing to researchers, practitioners, instructors and students (both undergraduate and graduate), as well as the general public. This updated reference integrates all basics concepts and research efforts under one umbrella. Coverage has been expanded to include new emerging topics such as crowdsourcing, opinion mining, and sentiment analysis. Revised content of existing material keeps the encyclopedia current. The second edition is intended for college students as well as public and academic libraries. It is anticipated to continue to stimulate more awareness of social network applications and research efforts. The advent of electronic communication, and in particul ar on-line communities, have created social networks of hitherto unimaginable sizes. 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.

ISBN: 9781493971312

Standard No.: 10.1007/978-1-4939-7131-2doiSubjects--Topical Terms:

528622
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Encyclopedia of Social Network Analysis and Mining
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