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Investigating Facebook groups through a random graph model

journal contribution
posted on 2014-01-01, 00:00 authored by Dinithi Pallegedara, Lei PanLei Pan
Facebook disseminates messages for billions of users everyday. Though there are log files stored on central servers, law enforcement agencies outside of the U.S. cannot easily acquire server log files from Facebook. This work models Facebook user groups by using a random graph model. Our aim is to facilitate detectives quickly estimating the size of a Facebook group with which a suspect is involved. We estimate this group size according to the number of immediate friends and the number of extended friends which are usually accessible by the public. We plot and examine UML diagrams to describe Facebook functions. Our experimental results show that asymmetric Facebook friendship fulfills the assumption of applying random graph models.

History

Journal

Journal of multimedia

Volume

9

Issue

1

Pagination

25 - 34

Publisher

Academy Publisher

Location

Finland

ISSN

1796-2048

Language

eng

Publication classification

C1 Refereed article in a scholarly journal; C Journal article

Copyright notice

2014, Academy Publisher

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