Methods Center
Center for Applied Network Analysis and System Science
How online communities function.
Image by Amber Case / CC BY-NC 2.0
Context
The Center for Applied Network Analysis and System Science applies rigorous network research methods to pressing policy challenges, providing objective solutions based on analytic results.
Network analysis is a set of methods and theories that help us understand relationships and how those relationships impact outcomes for individuals and interconnected systems. The center gathers together a distinctively interdisciplinary group of researchers who use network analysis to explore various policy challenges, including:
- Criminal hierarchies
- Air Force logistics
- HIV risk reduction in Africa and the Middle East
- Substance use among at risk and high risk populations
This work provides important insights about the structural, contextual, and social factors that influence physical, human, and organizational systems.
VIDEO: An Introduction to the Center for Network Analysis an System Science
Methodologies & Tools
Network methods consider systems holistically rather than focusing on isolated components. Thus, these methods provide comprehensive insights and solutions for important policy questions. By contrast, considering key players independently of the systems in which they are embedded is likely to obscure important relationships.
Researchers from the Center for Applied Network Analysis and System Science apply a range of network analysis methodologies, including
Visualization - Graphical representation of social networks can assist policy analysts in visually understanding the depth and breadth of relationships and their interdependent nature.
Network Indicators and Descriptives - The calculation of network indices (such as centrality) helps policy analysts identify key players from structural data that then can be used for peer-led and public-opinion leader interventions.
Network Statistical Models - These innovative models assist policy analysts and researchers in assessing the probability that relationships between behavior and networks exist. Through network statistical models, we can understand the ways in which relationships affect behavior and how behavior affects relationships.
A visualization of the network of civilian and military preparedness organizations in a particular country (from RAND TR-764 Bridging the Gap)
Real-World Applications
A Rockville, MD Playful City event
Photo by Healthy Living Rockville
Does housing policy have an impact on health behavior? Leveraging a natural experiment in Montgomery County, Maryland, in which residents were randomly assigned to different types of public housing, researchers applied network analysis methodology to find out.
Residents were assigned to either clustered public housing projects, or scattered-site subsidized housing (where public units are scattered among market-rate housing). Researchers surveyed the heads of 453 households, asking about their health as well as the perceived health of their network members (family, friends, and neighbors).
The results of this study reinforced existing evidence that public housing residents are vulnerable from a health perspective. Researchers found that the health status of one's social network members varies modestly between residents of clustered public housing projects and residents of units scattered into market-rate developments where neighbors are not poor. In particular, living in scattered public housing is associated with the perception that more network members exercise regularly.
Expertise
Researchers associated with the Center for Applied Network Analysis and System Science come from academic backgrounds that span a variety of fields and skill sets, including policy analysis, behavioral and social science, medicine, physics, mathematics, statistics, and engineering.
Center Co-directors
Work with Us
Interested in how network analysis methods can be applied to your research? Fill out the form below and we'll get back to you soon.
Methods Centers at Pardee RAND
-
Center for Causal Inference
CCI is devoted to improving the use of state-of-the-art causal inference methods for RAND research projects on important public policy issues by developing new methods in areas where there is a need and by making the application of such methods easily available and understood by all audiences.
Learn More » -
Center for Decision Making Under Uncertainty
The Center for Decision Making under Uncertainty assesses the depth and breadth of uncertainty and risk levers in policy domains and research pathways. DMU researchers develop and apply their expertise to projects that require analytical methods, tools and processes to manage decision-making under uncertainty.
Learn More » -
RAND Center for Scalable Computing and Analysis
The Center for Scalable Computing and Analysis engages in and supports the transformation of data science at Pardee RAND and within RAND as a whole, by fostering a community of expertise on best practices for use of large-scale data.
Learn More » -
Center for Gaming
The Center for Gaming works to grow Pardee RAND's methodological expertise and to use gaming, simulation and modeling to improve decisionmaking across a wide range of policy areas.
Learn More » -
RAND Center for Qualitative and Mixed Methods
The Center for Qualitative and Mixed Methods (C-QAMM) develops and promotes tools for generating empirically based insights through exploratory data collection and analysis.
Learn More » -
RAND Center for Applied Network Analysis and System Science
The Center for Applied Network Analysis and System Science applies rigorous network research methods to pressing policy challenges, providing objective solutions based on analytic results.
Learn More »