Network Analysis

[PhD Course] - Network Analysis

Network Analysis



Networks are everywhere. Global trade, supply chains, financial markets, the World Wide Web, professional and social communities are examples of interconnected systems that are important to the structure and function of the modern world. The pattern of connections in such systems can often be represented as a network, the components of the system being the nodes and the connections the links. Networks are a general yet powerful means of representing patterns of connections or interactions between parts of such systems. The first part of this course will introduce tools for the study of networks and show how common principles permeate the functioning of diverse networks and how the same issues related to robustness, fragility, and interlinkages arise in different types of networks. The second part of this course will use examples and applications of the network approach to reveal new and useful insights into trade, finance, business, and society.

This course will use some game theory, statistics, econometrics, and analytical reasoning. The course will aim to be self-contained and develop concepts and tools from the ground up, but some (undergraduate-level) background in these areas is highly recommended.


Session 7: Practical session: Using R, and Markdown

This section will consider the differences and similarities between markets and networks, as well as their interaction in the context of International Business.

Session 8: Observing and Measuring Social Interaction

This section will study the problems in the empirical measurement of network effects.

Session 9: Networks, creativity and innovation

This section will sketch how researchers have used networks to investigate some important business and social phenomena.

Session 10: Network analysis and system dynamics, diffusion, contagion and other processes

Session 11: MNEs and Networks

Community values and Honor Code

In this course, you will have access to some of the tools we use on our data science platform in our lab The use of these tools requires adherence to our Honour Code. This comes on top of the school’s regulations [here]

Community Values

It is essential to foster a supportive e-learning environment.

In our lab, we believe it is essential that all participants embody and uphold our community values in order to foster a supportive online learning environment where individuals can have open discussion, reflect on their thinking and learn from each other.

Our laboratory’s Honour Code

A code of honour, ethics and respect.

Our Honour Code complements the Community Values Statement and reflects the commitment of participants as members of the learning community to participate in, foster and sustain the learning model of our laboratory.