Lugano, Switzerland

Using Social Network Analysis to Understand Data

when 16 August 2022 - 20 August 2022
language English
duration 1 week
fee CHF 700

Social network analysis is used to understand communities by investigating their structure. How individuals in communities are connected to one another can influence information flows, actor importance, and the overall behavior of the community. Social network analysis allows us to identify key actors, hierarchies of relationships, brokers, groups that act in a coordinated way, patterns of information flow, and the resilience of the community as a whole.

Networks are typically represented by nodes (individuals) that are connected with other nodes by links (or edges). In social network analysis, the nodes in a network are usually people. More broadly, in network analysis nodes can be used to represent a variety of things, such as cities, online communities, scientific articles, colors, emotions, or simply words in language. In all cases, the goal of network analysis is to understand how the structure informs the behavior of the network and the items or individuals within it.

In this workshop, students will learn the basic concepts of social network analysis and extend its use to network analysis more broadly. Students will learn the material in a practical hands-on fashion, using a variety of free packages, including Pajek, Gephi, and igraph in R. They will also gain insight into how these are used in contemporary scientific publications.
If students have ongoing projects of their own, they will be able to investigate these with the various tools and gain new insights into their research. By the end of the workshop, students will have a vocabulary for understanding network analysis and should have the knowledge needed to understand and replicate most of the research in network analysis that they are likely to see in the social sciences.

Students will learn concepts like small world analysis (how structured is the network?), homophily (do similar nodes cluster together?), network closure (are nodes in the network in harmony with one another?), distance (how far away are objects in the network from one another?), clustering and community detection (do communities develop?), and centrality (are some nodes more important than others?).

Students taking this workshop should have prior experience in R or be willing to learn. All code will be provided, and R will be introduced in an introductory way. There will be some simple mathematics (counting, addition, multiplication, division), but understanding it will not be integral to the workshop.

Course leader

Thomas Hills is currently the Director of the Behavioural and Data Science MSc and the Bridges Doctoral Training Centre in Mathematical and Social Sciences, both of which aim to provide and develop quantitative approaches to data in the social sciences.

Target group

Students taking this workshop should have prior experience in R or be willing to learn. All code will be provided, and R will be introduced in an introductory way. There will be some simple mathematics (counting, addition, multiplication, division), but understanding it will not be integral to the workshop.

Course aim

In this workshop, students will learn the basic concepts of social network analysis and extend its use to network analysis more broadly. Students will learn the material in a practical hands-on fashion, using a variety of free packages, including Pajek, Gephi, and igraph in R. They will also gain insight into how these are used in contemporary scientific publications.

Credits info

The Summer School cannot grant credits. We only deliver a Certificate of attendance, i.e. we certify your presence

If you consider using Summer School workshops to obtain credits (ECTS), you will have to investigate at your home institution (contact the person/institute responsible for your degree) to find out whether they recognize the Summer School, how many credits can be earned from a workshop/course with roughly 35 hours of teaching, no graded work, and no exams.

Make sure to investigate this matter before registering, if this is important to you.

Fee info

CHF 700: Reduced fee: 700 Swiss Francs per weekly workshop for students (requires proof of student status).
These fees includes also participation in one of the preliminary workshops (two-day workshop preceding the Summer School).
To qualify for the reduced fee, you are required to send a copy of an official document that certifies your current student status or a letter from your supervisor stating your actual position as a doctoral or postdoctoral student. Send this letter/document by e-mail to methodssummerschool@usi.ch.
CHF 1100: Normal fee: 1100 Swiss Francs per weekly workshop for all others.
These fees includes also participation in one of the preliminary workshops (two-day workshop preceding the Summer School).

Scholarships

As the Summer School is financed through participant’s fees alone and has no funds of its own, it cannot offer any scholarship, grants or financial aid.