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»Social Network Analysis - From Graph Theory to Applications with Python«
2019-06-03, 16:00–16:25, Hall 2 (PyData)

Social network analysis is the study of social structures through the use of graph theory. In this talk I will present network theory and application of building and analyzing social networks for practical use-cases in Python with NetworkX.

Social network analysis is the process of investigating social structures through the use of networks and graph theory. It combines a variety of techniques for analyzing the structure of social networks as well as theories that aim at explaining the underlying dynamics and patterns observed in these structures. It is an inherently interdisciplinary field which originally emerged from the fields of social psychology, statistics and graph theory.

This talk will cover the theory of social network analysis, with a short introduction to graph theory and information spread. Then we will deep dive into Python code with `NetworkX`

to get a better understanding of the network components, followed-up by constructing and implying social networks from real `Pandas`

and textual datasets.
Finally we will go over code examples of practical use-cases such as visualization with `matplotlib`

, social-centrality analysis and influence maximization for information spread and social marketing.