Applying the Binary Classification Methods for Discovering the Best Friends on an Online Social Network (CROSBI ID 649930)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Stupalo, Maja ; Ilić, Juraj ; Humski, Luka ; Skočir, Zoran ; Pintar, Damir ; Vranić, Mihaela
engleski
Applying the Binary Classification Methods for Discovering the Best Friends on an Online Social Network
Online social networks (OSN) are one of the most widely adapted services of the Internet infrastructure, Facebook being one of the most popular among them. Facebook models connections between its users through the concept of "friendship". However, the type and intensity of these connections between different people on Facebook vary significantly. In most cases, friends on Facebook correspond to mere acquaintances in real-life, with only a smaller subset representing actual close friends. The aim of research presented in this paper is to provide a method for estimating the intensity of Facebook friendships, i.e., to distinguish connections representing close friends from others. The study was performed by analyzing Facebook interactions between users (e.g. number of mutual likes, comments, shared photos, etc.) using supervised learning algorithms for binary classification of data. Among the chosen algorithms, the best results were gained by using random forest algorithm – accuracy of 84.73%.
online social networks, Facebook, supervised learning algorithms, close friends, binary classification
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
155-161.
2017.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 14th International Conference on Telecommunications ConTEL 2017
Dobrijević, Ognjen ; Džanko, Matija
Zagreb: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu
978-953-184-224-2
Podaci o skupu
14th International Conference on Telecommunications ConTEL 2017
predavanje
28.06.2017-30.06.2017
Zagreb, Hrvatska