A Hybrid Epidemic Model for Antinormative Behavior in Online Social Networks

被引：0
|
作者：
Liao, Cong [1 ]
Squicciarini, Anna [1 ]
Griffin, Christopher [2 ]
Rajtmajer, Sarah [3 ]
机构：
[1] Penn State Univ, Coll Informat Sci & Technol, University Pk, PA 16802 USA
[2] US Naval Acad, Dept Math, Annapolis, MD 21402 USA
[3] Penn State Univ, Dept Math, University Pk, PA 16802 USA
来源：
PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015) | 2015年
关键词：
D O I：
10.1145/2808797.2809334
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we describe a novel approach to investigate negative behavior dynamics in online social networks as epidemic phenomena. We present a finite-state machine model for time-varying epidemic dynamics, and validate this model with experiments over a large dataset of Youtube commentaries, indicating how different epidemic patterns of behavior can be tied to specific interaction patterns among users. A full version of this paper is available on arXiv.org.
引用
收藏
页码：1563 / 1564
页数：2
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