DNA-Inspired Online Behavioral Modeling and Its Application to Spambot Detection

被引：116

作者：

Cresci, Stefano ^{[1
]}

Di Pietro, Roberto ^{[2
,3
,4
]}

Petrocchi, Marinella ^{[1
]}

Spognardi, Angelo ^{[5
]}

Tesconi, Maurizio ^{[1
]}

机构：

[1] IIT CNR, Inst Informat & Telemat, Pisa, Italy

[2] Nokia Bell Labs, Paris, France

[3] Univ Padua, I-35100 Padua, Italy

[4] IIT CNR, Pisa, Italy

[5] Tech Univ Denmark, DTU Compute, Lyngby, Denmark

来源：

IEEE INTELLIGENT SYSTEMS | 2016年 / 31卷 / 05期

关键词：

TWITTER;

D O I：

10.1109/MIS.2016.29

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A novel, simple, and effective approach to modeling online user behavior extracts and analyzes digital DNA sequences from user online actions and uses Twitter as a benchmark to test the proposal. Specifically, the model obtains an incisive and compact DNA-inspired characterization of user actions. Then, standard DNA analysis techniques discriminate between genuine and spambot accounts on Twitter. An experimental campaign supports the proposal, showing its effectiveness and viability. Although Twitter spambot detection is a specific use case on a specific social media platform, the proposed methodology is platform and technology agnostic, paving the way for diverse behavioral characterization tasks. © 2001-2011 IEEE.

引用

页码：58 / 64

页数：7

共 11 条

[1] A generic statistical approach for spam detection in Online Social Networks [J].