Analysis and Theory of Social Networks (3): Social Big Data and analysis of social networks

Social network analysis is a theoretical and methodological tool to understand social structures, how they emerge from individual behaviors and at the same time how they affect them. Thanks to the deep penetration of online social platforms, today we can observe and often analyze links on a scale that far exceeds what was possible just a few decades ago. While this drives new methodologies, the large-scale networks that we can observe can still be informed by classic questions in social network theory while also stimulating the production of new theory. In this course we take a quick tour of the classic ideas and methods of this paradigm. We demonstrate how they are not only applicable to contemporary digital networks,but how they have developed thanks to the data that we can extract from Twitter, Facebook and other digital platforms. We will accompany the theoretical and methodological tour with practical sessions to learn to handle network analysis and visualization tools such as Gephi and others.

Course by Emanuele Cozzo .

Course program

First session: Introduction to network thinking.

Tuesday May 11, 6pm - We will introduce the basic theoretical and methodological elements and see how they relate to the different schools of thought. VIDEO / PDF

Second session: Hands-on! Installation of tools

Tuesday May 18, 6pm - Practical session to learn and install the different tools that allow us to analyze and visualize networks.

Third session: Network analysis and modeling

Tuesday May 25, 6 pm - Through some case studies we will delve into some of the elements learned in the previous session, such as measures of centrality and the detection of communities. VIDEO / PDF

Fourth session: Social Big Data and social network analysis

Monday May 31st, 6pm - We will see how to extract data from online social platforms and how to analyze the social interaction networks that are developed there. VIDEO / PDF

More information here

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