Amicitia

2021

Amicitia
Type
Network Art
Credits

Prof. Douglas Guilbeault

FACTS

90118 nodes

304083 edges

This piece was made in collaboration with Prof. Douglas Guilbeault to illustrate a novel method for identifying the spread of complex contagions, published in Nature Communications. Some of the real-life applications are also covered by PNAS in a more accessible manner.

The Add Health dataset was constructed from an in-school survey administered to 90,118 students from over 70 distinct communities throughout the US in 1994-1995. Designed to gather data on students’ social networks, each student was given a paper-and-pencil questionnaire and a copy of a roster listing every student in the school.

Students were asked to “List your closest (male/female) friends. List your best (male/female) friend first, then your next best friend, and so on. (Girls/boys) may include (boys/girls) who are friends and (boy/girl) friends”.

This dataset was chosen for the study because the social networks possess high levels of topological variation in terms of population size, average number of connections per person, and average clustering. Each community of students is colored differently.

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