DA4610 Dynamic Network Analysis

This course builds on DA4600 (Dark Networks) by offering additional substantive and methodological tools for analyzing relational networks. The course is pragmatically oriented in that it pays particular attention to issues concerning the collection and preparation of relational data in software programs such as Palantir, Analysts Notebook, Microsoft Excel and Microsoft Access and moving to traditional social network analysis tools such as UCINET, Pajek and ORA (Organizational Risk Analyzer). This course will also explore what is being called dynamic network analysis where users not only examine the effects of actual ties (e.g., friendship, kinship) but also "virtual" ties (e.g., shared ideology, skills, knowledge, etc.) Finally, the course will introduce students to techniques using social network data (regression) and geospatial data (geospatial statistics) that will help students tease out which variables (e.g., centrality, education level) are causally related from those that are not.

Prerequisite

DA4600 and permission from the instructor

Lecture Hours

4

Lab Hours

0

Course Learning Outcomes

• Formal Analytics, Problem Solving, and Design Applications: Students will develop a functional understanding of R (a software environment for statistical computing) and basic techniques for importing, manipulating, and visualizing social network data; (b) learn to use R to examine the topography of networks, detect subgroups within networks, identify key actors, and statistically test hypotheses with social network data to assess conflict, will, motivations, power-dynamics, and decision-making; and (c) foster their knowledge of operational and organizational dynamics, by using SNA to analyze social media, narratives, and other texts.
• Information Strategy: Students will be able to demonstrate the ability to craft (at least) three intervention (influence) strategies to disrupt, destabilize, or destroy a dark network or increase the resilience, robustness, and/or efficiency of a light network.
• Transnational Dark Networks: Students will cultivate an understanding of the dynamics of network proliferation and recent and possible future trends, including (a) trafficking in WMD material, (b) components, humans, drugs, small arms, money, etc., and (c) avenues that criminal, terrorist, and other dark networks use to collaborate, unite, or compete.
• Writing and Presentation: Students will be able to write an effective 15–20 page paper and deliver a 5-10 minute presentation.