LATEST PROJECTS
Project | Geographical Infrastructure for the City of Boston
Co-workers: Daniel O'Brien, Saina Sheini, Alina Ristea
The Boston Area Research Initiative’s Geographical Infrastructure for Boston is a database that organizes and links the places and regions of Boston, MA across 17 levels—including land parcels, streets, census geographies, and other administrative regions. The levels are organized in a hierarchy, with the items in each level nested in the higher-level regions that contain it (e.g., land parcels in census geographies). This is coordinated via variables that act as unique identifiers at each level. As a composite, the database is intended to facilitate aggregate calculations across levels of the hierarchy and analyses of data from different sources that reference the same geographical units. In particular, the database makes it possible to connect data sets generated by the City of Boston with census geographies and data. Note: Only data sets that were updated in 2019 are posted here. See earlier versions of the Geographical Infrastructure for the other data sets (e.g., census, administrative geographies)
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Project | Critical Infrastructure Resilience Institute Energy and Transportation Governance Project - Global Resilience Institute
Co-workers: Dr. Matthias Ruth, Joshua Laufer, Vaishali Kushwaha
We worked with local entities that are widely perceived as neutral brokers or information, convened a diverse set of stakeholders to articulate the main challenges they face in preparing for and responding to hazards, interviewed and surveyed an even broader set of stakeholders to map regional and trans-regional interactions among them, and subsequently used that information to work with stakeholders on the identification or procedures and policies that improve resilience.
Project | Analyzing Social Resilience using Twitter data under Natural Events vs. Human-Driven Disasters; Is There a Difference? (2018-present)
Twitter data offers a giant pool of real-time information, geographically-focused information on different levels of users and tweets. Twitter is designed to ask for “what is happening?” at each moment. With data mining skills, Twitter data can be a great resource of discovering underlying patterns in communities. My research proposal offers a way of analyzing social capital as an indicator of social resilience utilizing geotagged and non-geo-tagged tweets. I intend to define measures of social capital in different communities using sentiment and network analysis methods. Of the most important applications of social capital is to show resilience towards disasters. Therefore, the general path of my research is finding patterns of social interactions on Twitter under normal situation and then analyze their changes under the main two types of disaster scenarios: natural events vs. human-driven disasters. I am also interested to find the difference in the “bounce-back to normal life” process after each type of disaster. I will approach these questions by developing metrics of social capital and social resilience using Twitter data. Along with the creation of these methodologies, a tool can be developed to calculate the social capital of each Twitter user and their communities and their online social network. The results of this project would help identify the weaker parts of the communities that need to be considered in the resilience planning of the cities.
The tools that I will use in this project are as following:
• Rstudio: Data cleaning, exploration, and manipulation, statistical analysis including regressions and machine learning
• QGIS and ArcGIS: Manipulation and analysis of geo-spatial data
• Tableau: Interactive data visualization
• Python: Scrapping data, backend web development, data analysis and training, and tool development
Saina Sheini, Mojtaba Hosseinalipour