本課程中將講述社群網路基本概念與其關聯性分析應用。以初等圖學理論為基礎介紹社群網路的關聯結構，並透過資料探勘、統計模型等技術分析社群網路議題。課程中將針對WWW、Facebook、Twitter、Netflix等大型社群網路平台，這些平台擁有由數百萬計以上的個體或組織所創立與使用的豐富資訊內容。本課程內容包含這樣的大社群網路的結構與資訊分析，介紹近期的社群網路模型。

This course will introduce the basic concepts of social networks and their correlation analysis applications. Introduce the correlation structure of social networks based on elementary graph theory, and analyze social network issues through data mining, statistical modeling and other technologies. The course will focus on large-scale social network platforms such as WWW, Facebook, Twitter, and Netflix. These platforms contain rich information content created and used by more than millions of individuals or organizations. The content of this course includes the structure and information analysis of such a large social network, and introduces recent social network models.

資料挖掘與分析是電腦科學的核心課程之一，本課程中將講述社群網路基本概念與其關聯性分析應用，透過資料探勘、統計模型等技術分析社群網路議題。

Data mining and analysis is one of the core courses of computer science. This course will introduce the basic concepts of social networks and their correlation analysis applications, and analyze social network issues through data mining, statistical models and other technologies.

1.Reza Zafarani, Mohammad Ali Abbasi, Huan Liu, 2014., “Social Media Mining: An Introduction”, Cambridge University Press

2.David Easley, Jon Kleinberg, 2010., “Networks, Crowds, and Markets”, Cambridge University Press

1.Reza Zafarani, Mohammad Ali Abbasi, Huan Liu, 2014., "Social Media Mining: An Introduction", Cambridge University Press

2.David Easley, Jon Kleinberg, 2010., “Networks, Crowds, and Markets”, Cambridge University Press