In this 2-hour course you will learn how to create beautiful and useful visualizations for network analysis, which can be used in your research and reports. We will introduce the basic concepts from network analysis, such as betweenness centrality, modularity and structural gaps. We will then propose a very efficient methodology that can be used both for social and knowledge network analysis, followed by a practical case study, which will guide you through the process step-by-step. By the...
In this workshop you will learn both basic and advanced approaches to social network visualisation and interpretation of visualised results. Network visualisation can be a very useful tool for discovering hidden patterns within interconnected data: detecting communities within social networks, identifying the most influential nodes, learning about the inner dynamics of a group, better understanding what actions need to be taken both within and outside of the social group studied in order to achieve specific results.
In the first part of this course we will introduce some basic concepts from network analysis: from betweenness centrality (that measures the node's influence in the network) to modularity (community structure). We will then introduce the software tools you can use to construct your own networks (InfraNodus), to visualize the graphs and perform advanced metrics calculations and analysis (Gephi).
In order to make the course more practical, we will be using an example of foods to nutrients network: the graph that shows which nutrients are contained in various foods. We will demonstrate how you can use network analysis to create healthy recipes and menus, as well as get a much better understanding of the datasets you're dealing with.
We will also demonstrate some advanced techniques and methodologies that can be used with the both software packages to ensure high quality presentation-ready visualisations.