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The study of social networks has expanded exponentially across the social and natural sciences in the past decade. Social network analysis has become a conventional approach to problems in physics, biology, business, sociology, anthropology, political science, organizational studies, and many other areas. This course aims to introduce undergraduate students to social network concepts and methods. Students gain hands-on experience collecting, coding, entering, analyzing, and visualizing social networks. For example, the class uses students_Ñé personal networks on Facebook as an accessible example to help see how to conceptualize and measure social networks; these networks are used as a point of departure to motivate students to examine a wider range of day-to-day social networks (e.g., among co-workers, among collaborating firms, among politicians). The approach of the course is to illustrate how social networks are omnipresent and can be examined using methodologies available to the students. Other exercises examine networks collected through Web crawlers, scientific-citation databases, field surveys, direct observation, and other existing databases. At the end of the course, each student completes an independent research project that collects, analyzes, and visualizes a unique data set that she or he has compiled. An LSAIT grant would support this course in three ways. First, it would support the purchase of perpetual licenses for UCINet, a needed software package which is not already available through LSAIT. Second, it would support the development of additional tutorials and documentation for other, freely available network software (such as SoNIA and VOSON), with which I am not intimately familiar. Third, it would support the collection of new datasets and frameworks for collecting data (e.g., Web crawlers) for student use. The grant would fulfill LSAIT's funding priorities in three ways. First, the grant would develop my expertise in using social networking software for the first time in a new course, which would be an early adoption of this technology within Organizational Studies. Second, the grant would support student learning on aspects of the information revolution by demonstrating the use of Web crawlers to collect data and by using Facebook as an accessible example to understand social networks. Third, the tutorials and documentation produced using the grant would have the potential for wider use in the College.