README.md

In MattiaGirardi1997/Understanding-Complex-Networks:

Bachelor Thesis

Understanding complex social networks. The impact of social features on the diffusion process.

Understanding social interactions and the emergence of social networks can help us understand the flow of market trends, product adoption and diffusion processes. Extant literature has proposed a wide variety of features that can be used to describe networks (e.g., degree distribution, reciprocity, transitivity). Furthermore, it has been shown that in social networks, many such features have surprising regularities (the degree distribution is often broad and reciprocity and transitivity are relatively high). The aim of this thesis is to identify which are the relevant features describing networks, how they relate to social mechanisms and which is their impact on the diffusion of products, ideas and behaviors. In the first step, the student will revise the relevant literature on network science, social mechanisms and diffusion process and define the coreconcepts. In the second step, the student will analyze empirical networks (social and non-social) and train a classifier that predicts if a network is social based on the selected features. In the third step, the student will conduct a simulation study to quantify the importance of each feature in the diffusion process. After finishing the thesis,the student will have a good knowledge of selected literature on network science and will be familiar with the use of R for scientific research.

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