Representation and analysis of spatiotemporal encounters published in online social networks

Autor: Valéria Cesário Times, Bruno Neiva Moreno, Stan Matwin
Rok vydání: 2021
Předmět:
Zdroj: Social Network Analysis and Mining. 11
ISSN: 1869-5469
1869-5450
DOI: 10.1007/s13278-021-00797-1
Popis: The growing use of online social networks (OSNs) has encouraged users to share detailed information about places they have visited, resulting on a clear connection between the virtual world and the physical world. The functionality responsible for sharing location by users dubbed “check-in”. This paper describes social and spatiotemporal interactions as “user encounters”, which occur when two people (social dimension) are somewhere (spatial dimension) at a given point in time (temporal dimension) and decide to publish they are together. In this paper, we present a network model to represent encounters: the SiST (Soc ial, Spatial and Temporal) model. We used real OSN data do detect and build networks based on the SiST model. The encounters found were analyzed from different points of view: (1) we investigated the laws governing encounters publication; (2) we studied the properties of networks generated from our model aiming at identifying patterns related to encounters occurrence and (3) we defined algorithms to identify typical users’ movements. According to the distribution analysis of SiST networks, encounter publication does not occur randomly; instead, they usually occur on weekends and especially during the night, between 11 p.m. and 3 a.m..
Databáze: OpenAIRE
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