¿Song Yang is professor of Sociology at Department of Sociology and Criminology University of Arkansas. My research emphasizes Social Network Analysis (SNA), focusing on SNA methodology and its application to analyzing wide range of research topics. I published more than 20 peer reviewed articles and several books, such as Social Network Analysis (with David Knoke, 2008) and Social Network Analysis (with David Knoke, 2020), and Social Network Analysis: Methods and Examples (with Franziska Keller and Lu Zheng, 2016). 

Chapter 1: Social Network Analysis: An Introduction.- Chapter 2: Social Network Analysis: Data Collections.- Chapter 3: Methods for Analyzing Networks.- Chapter 4 Advanced method in Social Network Analysis.- Chapter 5: A Whole Network Study: Gender and Racial Homophily in Classroom Discussion Network.- Chapter 6: An ego-centric network study of core discussion network during the Covid-19 Pandemic.

This book offers a balanced view between a basic introduction of Social Network Analysis (SNA) in its methods and application, and advanced topics of data mining techniques and the subsequent SNA analyses. The book stands out as uniquely important contribution to the SNA field because it moves beyond the stage of basic SNA methods. It describes data mining techniques, introducing an online discourse collection platform, ICAS, which is developed by an interdisciplinary team involving Sociologists and Computer Engineer teams with supports of NSF funds.
Targeted audiences of this book are students and scholars interested in using SNA techniques to advance their analytics of their respective research areas. This book provides particular utilities to students at the beginner stage of learning SNA basics, and those in their intermediary careers looking to advance their knowledges of what SNA has to offer. The unique features of this book lie in its descriptions of data mining techniques, data processing, and data analytics. The discussions of an online discourse network platform and data processing capabilities present tremendous benefits to those who aspire to mine the massive data of online social networking.