1.

Record Nr.

UNINA9910254840603321

Titolo

Trends in Social Network Analysis : Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment / / edited by Rokia Missaoui, Talel Abdessalem, Matthieu Latapy

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017

ISBN

3-319-53420-3

Edizione

[1st ed. 2017.]

Descrizione fisica

1 online resource (XIII, 255 p. 90 illus., 68 illus. in color.)

Collana

Lecture Notes in Social Networks, , 2190-5428

Disciplina

302.3

Soggetti

Data mining

Social sciences—Data processing

Social sciences—Computer programs

Artificial intelligence

Database management

Physics

Data Mining and Knowledge Discovery

Computational Social Sciences

Artificial Intelligence

Database Management

Applications of Graph Theory and Complex Networks

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

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.

Sommario/riassunto

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.