In this accessible workshop, we will provide an introduction to using the PARTNERTM CPRM (Community Partner Relationship Manager) software to collect and analyze social network data for continuous network monitoring and improvement in community settings. This platform reduces the complexity of network data collection, provides automated analysis and visualizations, and creates opportunities for community ownership and public-facing data sharing. We will highlight the key components of capturing data with PARTNERTM CPRM, including: > Member Management: Participants will learn how to populate a PARTNERTM CPRM ecosystem with a list of network members, assign attributes to those members, and include them in a data capture. We will also discuss how to build on existing approaches community networks and organizations may be using to track their members (e.g., via spreadsheet or database). > Question Design & Data Collection: Participants will learn about how to use the standard survey questions included in the PARTNERTM CPRM platform as well as how to design their own. They will also learn about how to schedule in-platform email recruitment and track responses as they come in. We will also demonstrate ways to track networks as they develop over time and to capture data about “networks of networks” using the tool. > Analysis & Dissemination: All participants will have a chance to explore the analysis tools on the platform, including network visualization, key metrics, GIS mapping, and chart/table development. Participants will also learn how to disseminate results through the platform using member profiles (individualized profiles for each member of the network) and dashboards (which can track whole network data as it comes in). Participants will leave the session with improved capacity for using PARTNERTM CPRM to: (1) design and implement community-engaged social network analysis projects, (2) track community networks over time, and (3) disseminate results of network analyses in practical contexts. Participants should bring their own computer to access workshop resources and follow along with tutorials to use the software.

From infectious diseases to innovations, from policies to norms, networks often influence how outcomes are distributed. This workshop introduces the many analytic and visualisation tools available in the ‘manynet’, ‘migraph’ and associated packages in R for studying network diffusion, contagion, or learning. First, we look at the tools available for simulating various contagion processes, including simple and complex diffusion. We extend these models to a range of different compartment models, e.g. SEIRS, that can better represent more varied processes, and suggest how to evaluate the fit of these simulations with observed diffusions. Second, we look at tools for measuring, describing, or inferring aspects of these processes, from hazard rates to thresholds. We show how they can be used on observed diffusions too, so please bring data from any salient projects you are working on. Lastly, we will explore how, with the rest of the tools available in ‘manynet’ and ‘migraph’, we can identify points of intervention to accelerate or obstruct diffusion. Because these procedures are based on ‘manynet’, they work with many different network formats and types, including ‘igraph’ and ‘network’ classes, as well as directed, multimodal, signed and multiplex data. Familiarity with R and RStudio is recommended.