Abstract
In the present work, data analysis of Erasmus+ Sport programs was performed using Network Theory. Funding amounts and partner coun-tries per program are the information of the target data. Developing a Python-based program, a network of countries' partnerships has been developed to examine whether specific countries cooperate more frequently, and which countries participate in more Erasmus+ Sport pro-grams. Thus, some basic indicators of centrality from network theory were calculated, which are presented together with their mathematical interpretation.It has also been studied whether the number of a country's participation in these programs is affected by its economic or social national characteristics. Specifically, GDP, happiness and education indexes are all examined if they affect a country's participation. Finally, given how the funding amount of a program is split between the partner countries, the total amount of funding received by each country for the period 2014-2018 was calculated. Â
Highlights
The data comes from the 'Partnerships' program, which is provided free of charge by Erasmus+ and is available on the program's official website [1], [2]
Correlation between financial/social indices and centralities. It is examined whether strength centrality is correlated with social and financial indices, such as Gross Domestic Product (GDP), happiness index and education index. Such an approach might be interested because: If, for instance, strength is positively correlated with GDP, that would mean that the highest the GDP of a country, the more frequently that country participates in Erasmus Sports programmes
All Erasmus+ Sports programmes are based on grants, which is shared between the participating countries
Summary
The data comes from the 'Partnerships' program, which is provided free of charge by Erasmus+ and is available on the program's official website [1], [2]. They describe the structure of the programs and provide details on each of the 600 programs carried out in
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