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Social Network Data Analytics – A Short Introduction

Event Details
Audience: Manager, Director and Senior Executives
Duration: 3 hours
Location: Miami Herbert Business School, University of Miami


About 70% of the U.S. population uses at least one social media site. In 2017, the PEW research center reported that 70% of businesses interact with customers via channels like Facebook, Twitter and other social platforms. Social media have become increasingly popular in recent years because of the increasing proliferation and affordability of internet enabled devices. This is evidenced by the rapidly growing popularity of many online social interaction platforms such as Twitter, Facebook and LinkedIn. The tremendous growth of these social media sites has led to an explosion of social network data, summarized in various forms. Social networks can be defined via the context of the social media sites. For example, for sites such as Facebook or Twitter, the definition of a network is straightforward as these sites are explicitly designed for social interactions. For other sites that are designed for services such as content sharing or Q&A, such as Pinterest and Quora, networks can be defined based on the frequency of user interaction.

Social networks (and many other networks such as financial, logistics and healthcare networks) are fundamentally important to businesses. Understanding how the network functions is a critical task. As a result, business leaders are expected to utilize analytical tools to gain a deeper understanding of the network - enabling them to make smarter, data-driven decisions about their businesses.

Network data analytics involves the analysis of network data and statistics to identify trends and patterns. This seminar provides a short introduction to the emerging fields of network data analytics and social science including social networks, social contagion, social community detection and other topics in network data mining. In particular, the seminar will cover the following topics:


Emma Jingfei Zhang

Dr. Emma Jingfei Zhang is a faculty member in the Department of Management Science at Miami Herbert Business School. She specializes in the statistical modeling and inference of complex network data, which facilitates the understanding of the interconnectedness of the social and business world around us. Her research combines computational statistics, dynamic processes and social science to exploit opportunities offered by large-scale datasets.


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