University of Twente Student Theses


Geometrical Social Networks

Chinthu Rukmani Kumar, Jayanth (2021) Geometrical Social Networks.

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Abstract:The rise of social networks in the past few years has been remarkable. The main reason behind the tremendous success of the social media is none other than Facebook. Facebook paved the way for other popular social networking applications such as Twitter and Instagram. Facebook is an online social networking application where users can become friends and socialize with anyone throughout the world. To find how two users from various different regions are connected, Facebook came with an idea called the Social Connectedness Index (SCI) to quantitize the strength of the connection. We expected that the relationship between users and their friend, the SCI, and the distance between users and their friends has some characteristic dependence and independence information. Such independence information is nowadays often represented by means of Bayesian networks. A Bayesian network is a type of probabilistic graphical model that captures dependence and independence information as a graph and a joint probability distribution. In this research, the main emphasis is on finding the right structure of the Bayesian network for predicting the SCI.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics, 54 computer science
Programme:Computer Science MSc (60300)
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