Abstract
Geosocial network neighborhood application allows user to share information and communicate with other people within a virtual neighborhood or community. A large and crowded neighbourhood will degrade social quality within the community. Therefore, optimal population segmentation is an essential part in a geosocial network neighborhood, to specify access rights and privileges to resources, and increase social connectivity. In this paper, we propose an extension of the density-based clustering method to allow self-organized segmentation for neighbourhood boundaries in a geosocial network. The objective of this paper is two-fold: First, to improve the distance calculation in population segmentation in a geosocial network neighbourhood. Second, to implement self-organized population segmentation algorithms using threshold value and Dunbar number. The effectiveness of the proposed algorithms is evaluated via experimental scenarios using GPS data. The proposed algorithms show improvement in segmenting large group size of cluster into smaller group size of cluster to maintain the stability of social relationship in the neighbourhood.
Highlights
Since Web 2.0 technology has gained its popularity, the use of online social networks (OSN) like Facebook and Instagram has increased to the point of becoming pervasive
We show how the current population segmentation in geosocial network neighbourhood using density-based clustering method can be extended to improve the quality of social community
Three improvements are implemented in the proposed algorithms namely improving distance accuracy between residents using haversine formula, eliminating user-defined parameter by defining threshold value to self-organize segment density, and improving social connectivity through re-segmentation using Dunbar number
Summary
Since Web 2.0 technology has gained its popularity, the use of online social networks (OSN) like Facebook and Instagram has increased to the point of becoming pervasive. With the introduction of social networking, people have more interaction in a neighbourhood level. Social networks tend to take over some of the functions of neighbourhood communities [1]. These virtual communities allow better quality of social interaction among neighbours in a social network. Geosocial network neighbourhood is one of the branches in social networking that allow user to share information and communicate with other people within a virtual neighbourhood or community. Geosocial networking application uses location awareness to track geolocation information that consists of current user location coordinates; longitude and latitude. Location-aware features in users’ mobile device will assist GPS self-check-in function to match users’ house address and current location
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