Social media data offers unprecedented opportunities for human geography research. Compared to traditional data collection methods, such as surveys and interviews, data collected via social media is more cost-effective, georeferenced, timelier, and available in greater volumes which therefore complement traditional approaches. As a form of spatial-temporal big data, social media provides unique insights into spatial-temporal patterns in peoples, places, and environments as well as their relationships and social dynamics—key research areas in human geography. This chapter introduces four key categories of social network analysis commonly conducted to address research questions in human geography—topic/event detection and tracking, public perspective exploration, collaboration and communication network analysis, and human mobility dynamics analysis—and provides a review of example applications for each. While numerous opportunities are available, challenges persist, including sample representativeness, sentiment analysis misclassification, geotag inaccuracies, and rising costs of data collection. The field remains dynamic and invites researchers to collaboratively address human geography questions through social network analysis.