With this posting I begin
the real work of my dissertation research project. I have successfully defended
my topic proposal and can finally implement my own research plan. It has
already been a long journey, and there is much more to come. Along the way I
will share the ups and downs of this research project, interesting findings,
and the many lessons, but today I introduce my dissertation project, From
Networks to Recovery: Effects of social networks on community recovery in the
face of flooding disasters.
How do social networks
influence individual and community behavior in disasters? Because of the
increasing frequency of flooding events and the large proportion of populations
that are impacted by these events, many communities will struggle to survive,
recover and thrive. Research into how communities nurture and leverage their
social capital, i.e. social network connections, to obtain information and
resources in times of stress will improve understanding of community
resilience. In future I hope this understanding will help community leaders and
decision-makers develop better policies to support the networks and behaviors
that improve community resilience.
What are the significant
underlying factors that impact social network change and utilization during
disaster recovery, and what sets of variables and interactions in these
networks lead to recovery? How much impact does space have on social networks?
To answer these questions I plan to develop an agent-based model of social
networks grounded in space to study the ability of these communities to rebuild
their social networks and recover resources in the context of flooding. Once
developed, I will use the model to test how variations in flooding impact,
urban density, population characteristics and network forms impact the disaster
recovery.
By using a holistic
approach, integrating ethnographic research and disaster theory with
computational experimentation, I intend to provide an example of how local,
individual relationships aggregate into collective action and interact with
global processes. My work will inevitably be limited by the quantity and
quality of empirical data that directly apply to the research questions. Of
practical necessity, the model will be a simplification of real-world behavior
and event outcomes. Nevertheless computational methods will allow me to monitor
and trace a subset of the variables interacting in the complex adaptive system
of a community in disaster.
I am excited to begin this
stage of the PhD process, and I welcome you to join me!
