From Security to Community Detection in Social Networking Platforms (Hardcover, 1st ed. 2019)


This book focuses on novel and state-of-the-art scientific work in the area of detection and prediction techniques using information found generally in graphs and particularly in social networks. Community detection techniques are presented in diverse contexts and for different applications while prediction methods for structured and unstructured data are applied to a variety of fields such as financial systems, security forums, and social networks. The rest of the book focuses on graph-based techniques for data analysis such as graph clustering and edge sampling. The research presented in this volume was selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. This book will appeal to practitioners, researchers and students in the field.

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Product Description

This book focuses on novel and state-of-the-art scientific work in the area of detection and prediction techniques using information found generally in graphs and particularly in social networks. Community detection techniques are presented in diverse contexts and for different applications while prediction methods for structured and unstructured data are applied to a variety of fields such as financial systems, security forums, and social networks. The rest of the book focuses on graph-based techniques for data analysis such as graph clustering and edge sampling. The research presented in this volume was selected based on solid reviews from the IEEE/ACM International Conference on Advances in Social Networks, Analysis, and Mining (ASONAM '17). Chapters were then improved and extended substantially, and the final versions were rigorously reviewed and revised to meet the series standards. This book will appeal to practitioners, researchers and students in the field.

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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Lecture Notes in Social Networks

Release date

April 2019

Availability

Expected to ship within 12 - 17 working days

First published

2019

Editors

, ,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

237

Edition

1st ed. 2019

ISBN-13

978-3-03-011285-1

Barcode

9783030112851

Categories

LSN

3-03-011285-3



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