Determination of Friendship Intensity between Online Social Network Users Based on Their Interaction (CROSBI ID 252714)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Krakan, Sanja ; Humski, Luka ; Skočir, Zoran
engleski
Determination of Friendship Intensity between Online Social Network Users Based on Their Interaction
Online social networks (OSN) are one of the most popular forms of modern communication and among the best known is Facebook. Information about the connection between users on the OSN is often very scarce. It is only known if users are connected, while the intensity of the connection is unknown. The aim of the research described was to determine and quantify friendship intensity between OSN users based on analysis of their interaction. We built a mathematical model, which uses: supervised machine learning algorithm Random Forest, experimentally determined importance of communication parameters and coefficients for every interaction parameter based on answers of research conducted through a survey. Taking user opinion into consideration while designing a model for calculation of friendship intensity is a novel approach in opposition to previous researches from literature. Accuracy of the proposed model was verified on the example of determining a better friend in the offered pair.
Facebook ; machine learning ; mathematical model ; online social network ; random forest ; supervised learning ; tie strength ; user interaction
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Podaci o izdanju
25 (3)
2018.
655-662
objavljeno
1330-3651
1848-6339
10.17559/TV-20170124144723
Trošak objave rada u otvorenom pristupu
Povezanost rada
Elektrotehnika, Računarstvo