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Trends in Social Network Analysis

Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment

  • Book
  • © 2017

Overview

Editors:
  1. Rokia Missaoui

    1. Department of Computer Science & Engineering, University of Quebec in Outaouais, Gatineau, QC, Canada

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    You can also search for this editor in PubMed   Google Scholar

  2. Talel Abdessalem

    1. Department of Computer Science and Networks, Telecom ParisTech, Paris, France

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    You can also search for this editor in PubMed   Google Scholar

  3. Matthieu Latapy

    1. UPMC Univ Paris 06, CNRS LIP6 UMR 7606, Sorbonne Universitès, Paris, France

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    You can also search for this editor in PubMed   Google Scholar

  • Presents overviews of problems and recommended solutions in social network analysis such as link prediction, influence maximization, and block modelling in complex networks
  • Explores new areas such as sarcasm and sentiment analysis, block modelling in dynamic networks using stochastic approaches, and behavior modelling of social network users
  • Features novel research topics such as social network user delurking, and threat assessment in social engineering
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Social Networks (LNSN)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xiii
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  2. The Perceived Assortativity of Social Networks: Methodological Problems and Solutions

    • David N. Fisher, Matthew J. Silk, Daniel W. Franks
    Pages 1-19

  3. A Parametric Study to Construct Time-Aware Social Profiles

    • Sirinya On-at, Arnaud Quirin, André Péninou, Nadine Baptiste-Jessel, Marie-Françoise Canut, Florence Sèdes
    Pages 21-50

  4. Sarcasm Analysis on Twitter Data Using Machine Learning Approaches

    • Santosh Kumar Bharti, Ramkrushna Pradhan, Korra Sathya Babu, Sanjay Kumar Jena
    Pages 51-76

  5. The DEvOTION Algorithm for Delurking in Social Networks

    • Roberto Interdonato, Chiara Pulice, Andrea Tagarelli
    Pages 77-106

  6. Social Engineering Threat Assessment Using a Multi-Layered Graph-Based Model

    • Omar Jaafor, Babiga Birregah
    Pages 107-133

  7. Through the Grapevine: A Comparison of News in Microblogs and Traditional Media

    • Byungkyu Kang, Haleigh Wright, Tobias Höllerer, Ambuj K. Singh, John O’Donovan
    Pages 135-168

  8. Prediction of Elevated Activity in Online Social Media Using Aggregated and Individualized Models

    • Jimpei Harada, David Darmon, Michelle Girvan, William Rand
    Pages 169-187

  9. Unsupervised Link Prediction Based on Time Frames in Weighted–Directed Citation Networks

    • Mehmet Kaya, Mujtaba Jawed, Ertan Bütün, Reda Alhajj
    Pages 189-205

  10. An Approach to Maximize the Influence Spread in the Social Networks

    • Ibrahima Gaye, Gervais Mendy, Samuel Ouya, Diaraf Seck
    Pages 207-228

  11. Energy Efficiency Analysis of the Very Fast Decision Tree Algorithm

    • Eva Garcia-Martin, Niklas Lavesson, Håkan Grahn
    Pages 229-252

  12. Back Matter

    Pages 253-255
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Keywords

About this book

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, stochastic 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.

Reviews

“This volume is a selective post-proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining. … The papers are uniformly of high quality and represent a good snapshot of the state of the art in the areas that they discuss. … The high quality of these carefully revised conference papers makes the volume of interest to researchers specializing in social networks who seek to stay abreast of recent developments.” (Computing Reviews, September, 2017) 

Editors and Affiliations

  • Department of Computer Science & Engineering, University of Quebec in Outaouais, Gatineau, QC, Canada

    Rokia Missaoui

  • Department of Computer Science and Networks, Telecom ParisTech, Paris, France

    Talel Abdessalem

  • UPMC Univ Paris 06, CNRS LIP6 UMR 7606, Sorbonne Universitès, Paris, France

    Matthieu Latapy

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