Trends in social network analysis : information propagation, user behavior modeling, forecasting, and vulnerability assessment
Title By: Missaoui, Rokia [Edited by] | Abdessalem, Talel [Edited by] | Latapy, Matthieu [Edited by]
Material type: BookSeries: Lecture notes in social networks.Publisher: Cham : Springer, c2017.Description: xiii, 255 p. : ill. ; 25 cm.ISBN: 9783319534190Subject(s): Computer science | Database management | Data mining | Artificial intelligenceDDC classification: 006.312 TR EN Online resources: Access electronically via SpringerLink ebooks - Computer Science without Lecture Notes (2017) | Location MapItem type | Home library | Call number | Status | Notes | Date due | Barcode | Item holds |
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REGULAR | University of Wollongong in Dubai Main Collection | 006.312 TR EN (Browse shelf) | Available | April 2018 | T0058429 |
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006.312 TA IN Introduction to data mining / | 006.312 TO DA Data mining with R : | 006.312 TO DA Data mining with R : | 006.312 TR EN Trends in social network analysis : | 006.312 VE US Using openrefine : | 006.312 VE US Using openrefine : | 006.312 WA IN Innovative techniques and applications of entity resolution / |
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.
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.