The Relationship between Online Social Network Ties and User Attributes

Amin MAHMOUDI, Mohd Ridzwan YAAKUB, Azuraliza Abu BAKAR

Research output: Journal PublicationsJournal Article (refereed)

3 Citations (Scopus)

Abstract

The distance between users has an effect on the formation of social network ties, but it is not the only or even the main factor. Knowing all the features that influence such ties is very important for many related domains such as location-based recommender systems and community and event detection systems for online social networks (OSNs). In recent years, researchers have analyzed the role of user geo-location in OSNs. Researchers have also attempted to determine the probability of friendships being established based on distance, where friendship is not only a function of distance. However, some important features of OSNs remain unknown. In order to comprehensively understand the OSN phenomenon, we also need to analyze users’ attributes. Basically, an OSN functions according to four main user properties: user geo-location, user weight, number of user interactions, and user lifespan. The research presented here sought to determine whether the user mobility pattern can be used to predict users’ interaction behavior. It also investigated whether, in addition to distance, the number of friends (known as user weight) interferes in social network tie formation. To this end, we analyzed the above-stated features in three large-scale OSNs. We found that regardless of a high degree freedom in user mobility, the fraction of the number of outside activities over the inside activity is a significant fraction that helps us to address the user interaction behavior. To the best of our knowledge, research has not been conducted elsewhere on this issue. We also present a high-resolution formula in order to improve the friendship probability function.
Original languageEnglish
Article number26
Pages (from-to)1-15
Number of pages15
JournalACM Transactions on Knowledge Discovery from Data
Volume13
Issue number3
DOIs
Publication statusPublished - May 2019
Externally publishedYes

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