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 covers 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.

中文翻译：

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社交网络分析：从图论到Python应用

社交网络分析是通过使用网络和图论来调查社会结构的过程。它结合了用于分析社交网络结构的各种技术以及旨在解释在这些结构中观察到的潜在动态和模式的理论。它是一个固有的跨学科领域，最初起源于社会心理学，统计学和图论领域。本讲座将涵盖社交网络分析理论，并简要介绍图论和信息传播。然后，我们将使用NetworkX深入研究Python代码，以更好地了解网络组件，随后通过从实际的熊猫和文本数据集构建并暗示社交网络。