Trends in Social Network Analysis: Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment
The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, shastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.
1133114742
Trends in Social Network Analysis: Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment
The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, shastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.
129.99 In Stock
Trends in Social Network Analysis: Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment

Trends in Social Network Analysis: Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment

Trends in Social Network Analysis: Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment

Trends in Social Network Analysis: Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment

Paperback(Softcover reprint of the original 1st ed. 2017)

$129.99 
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Overview

The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, shastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.

Product Details

ISBN-13: 9783319851495
Publisher: Springer International Publishing
Publication date: 07/24/2018
Series: Lecture Notes in Social Networks
Edition description: Softcover reprint of the original 1st ed. 2017
Pages: 255
Product dimensions: 6.10(w) x 9.25(h) x (d)

Table of Contents

1. The Perceived Assortativity of Social Networks: Methodological Problems and Solutions.- 2. A Parametric Study to Construct Time-aware Social Profiles.- 3. A Parametric Study to Construct Time-aware Social Profiles.- 4. The DEvOTION Algorithm for Delurking in Social Networks.- 5. Social Engineering Threat Assessment using a Multi-layered Graph-based Model.- 6. Through The Grapevine: A Comparison of News in Microblogs and Traditional Media.- 7. Prediction of Elevated Activity in Online Social Media Using Aggregated and Individualized Models.- 8. Unsupervised Link Prediction Based on Time Frames in Weighted-Directed Citation Networks.- 9. An Approach to Maximize the Influence Spread in Social Networks.- 10. Energy Efficiency Analysis of the Very Fast Decision Tree Algorithm.
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