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Trends in Social Network Analysis

Overview of attention for book
Cover of 'Trends in Social Network Analysis'

Table of Contents

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

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Chapter title
The DEvOTION Algorithm for Delurking in Social Networks
Chapter number 4
Book title
Trends in Social Network Analysis
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-53420-6_4
Book ISBNs
978-3-31-953419-0, 978-3-31-953420-6
Authors

Roberto Interdonato, Chiara Pulice, Andrea Tagarelli

Editors

Rokia Missaoui, Talel Abdessalem, Matthieu Latapy

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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