This course aims to introduce students to the field of Social Network Analysis (SNA). Social networks are ubiquitous nowadays but way before Elon Musk took over Twitter and Mark Zuckerberg got lost in the metaverse, SNA emerged in the 1960s as a very rich social science specialty trying to give substance to individuals, not through their inner psychological, and demographic, or professional characteristics but through the relationships, they entertain with their social environment.
The first objective of this class will be to introduce the concepts, and metrics designed and theorized by this specific stream of sociology in the 60s and the 70s: centrality measures, homophily, transitivity, cohesion, diffusion processes, etc. To do so, this course will examine the seminal papers in SNA. However, this intellectual journey will be complemented by a more hands-on approach, as half of the course will be devoted to teaching the students basic operations in Python such that they can collect data from digital social media platforms, before modeling, measuring, and visualizing this data using recent network analysis libraries. We will put the ancient concepts of SNA to the test and asses how fruitful they are to understand online interaction data.
The class will alternate readings of historical sociology papers and more contemporaneous articles typical of the digital age mixing concepts from SNA in the larger realm of computational social sciences. Most classes will be split into three parts: the discussion around a scientific paper, a lecture about a new SNA-related concept, and a third part where students will be invited to experiment on their own laptops with the newly introduced concepts, metrics, or algorithms with empirical data.
Jean-Philippe COINTET
Séminaire
English
No previous knowledge in either graph theory or programming is required. The class will still require to read papers adopting formal approaches. So students should be ready to engage with such content.
Spring 2022-2023
Everyone in the class will be asked to read and present a scientific paper in line with the topic of the session. One paper per week will be presented by two or three students.
An individual paper will also be required during the semester where students will be asked to choose an article in the press and connect it to the notions introduced in class.
Finally, a collective project will be conducted by students who are expected to build a network from social media platforms and analyze its structure.
Borgatti SP, Mehra A, Brass DJ, Labianca G. Network analysis in the social sciences. science. 2009 Feb 13;323(5916):892-5.
Doreian P. An intuitive introduction to blockmodeling with examples. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique. 1999 Jan;61(1):5-34.