Trends in Social Network Analysis

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

AvRokia Missaoui,Talel Abdessalem

Häftad, Engelska, 2018

Del i serien Lecture Notes in Social Networks

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2018-07-25
Mått:155 x 235 x 15 mm
Vikt:417 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Social Networks
Antal sidor:255
Förlag:Springer International Publishing AG
ISBN:9783319851495

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Databaser inom Data och IT
Artificiell intelligens inom Data och IT

Recensioner i media

“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)

Innehållsförteckning

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.