Description:

In recent years, there has been more and more interest in studying economy-related questions by means of network science. A reason for this interest builds on the realization that the economy's behavior cannot be investigated by individually studying the constituting components but only by considering the interplay between all relevant parts. This is in strong contrast to the standard economic theory.

In this talk, we will understand how network science helps to explore and analyze economic phenomena at varying scales and granularity.

World trade is generally highlighted as the largest economic network. We will analyze it in detail using NetworkX and really understand the significance of various network measures.

Talk Outline:

A. Introduction to Complex Network Analysis

B. Why Network Analysis in Economics?

i. Understanding interconnected economic components

ii. The significance of structural interdependencies

iii. Types of Economic Networks

C. World Trade Analysis using NetworkX

i. Utilizing the BACI-CEPPI dataset for bilateral trade relations

ii. Constructing the World Trade Network Graph

iii. Geographic visualization vs. topological visualization

iv. Analyzing network density and heterogeneity

v. The power-law distribution and its impact on global trade fluctuations

D. Centrality Measures and Clustering

i. Identifying influential countries with centrality measures

ii. Revealing Regional Trade Blocs with clustering

E. Analyzing Trade Networks of Different Commodities (Natural Gas, Coffee, Diamonds)

Prerequisites:

1. Python Programming Skills
2. Familiarity with Social Networks

Speaker Info:

Navya Agarwal is a third year Computer Science student at IGDTUW. She has worked on NetworkX as an Outreachy intern. She is currently researching Coordinated Campaigns on Social Media using complex network analysis. She is passionate about Open Source, specifically the scientific python ecosystem.

Speaker Links:

Personal Website

GitHub

LinkedIn