Title :
Social network classification incorporating link type values
Author :
Heatherly, Raymond ; Kantarcioglu, Murat ; Thuraisingham, Bhavani
Author_Institution :
Jonsson Sch. of Eng. & Comput. Sci., Univ. of Texas at Dallas, Dallas, TX
Abstract :
Classification of nodes in a social network and its applications to security informatics have been extensively studied in the past. However, previous work generally does not consider the types of links (e.g., whether a person is friend or a close friend) that connect social networks members for classification purposes. Here, we propose modified Naive Bayes Classification schemes to make use of the link type information in classification tasks. Basically, we suggest two new Bayesian classification methods that extend a traditional relational Naive Bayes Classifier, namely, the Link Type relational Bayes Classifier and the Weighted Link Type Bayes Classifier. We then show the efficacy of our proposed techniques by conducting experiments on data obtained from the Internet Movie Database.
Keywords :
Bayes methods; classification; social networking (online); information classification; link type relational Bayes classifier; naive Bayes classification; social network member; weighted link type Bayes classifier; Application software; Bayesian methods; Computer science; Computer security; Facebook; Heat engines; Informatics; Internet; Motion pictures; Social network services;
Conference_Titel :
Intelligence and Security Informatics, 2009. ISI '09. IEEE International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
978-1-4244-4171-6
Electronic_ISBN :
978-1-4244-4173-0
DOI :
10.1109/ISI.2009.5137265