Food for Thought: Analyzing Public Opinion on the Supplemental Nutrition Assistance Program (Partner: Atlanta Community Food Bank, Mentor: Carl DiSalvo)
UN Climate Challenge: Predicting & Alleviating Road Flooding in Senegal (Partner: UN Global Pulse, Mentor: Bistra Dilkina)
Food for Thought: Analyzing Public Opinion on the Supplemental Nutrition Assistance Program
This Data Science for Social Good team is working in conjunction with the Atlanta Community Food Bank to create a project that analyzes patterns in food controversies and messaging in order to support more robust public communication. The DDSG + ACFB project is focused on analyzing the coverage of SNAP on a national and state level, summarizing key themes across media coverage, and providing a comprehensive data driven assessment of the most influential and effective messages about SNAP. Students will work together to build data sets, analyze initial data sets, and develop effective tools and techniques that can be used by the Atlanta Community Food Bank moving forward to find and acquire data.
The Atlanta Legal Aid Society provides free civil legal services to low-income people to improve their “social, political, and economic conditions.” Since their founding in 1924, they have won many landmark cases and coined the term “predatory lending.” Atlanta Legal Aid is currently involved in a housing justice lawsuit against Harbour Portfolio Advisors, a company that profits from selling homes through “contract-for-deed” agreements. These land contract arrangements are frequently marketed as an alternative way for low-income people to buy homes if they may not qualify for a traditional mortgage. They typically involve a down payment, high interest rate, and sale price well above the actual assessed value of the home. Prospective buyers pay a monthly rate, as with a typical mortgage, and often have to take on high home-repair costs and property taxes; however, they do not receive the legal title to the home until the full purchase price has been paid. If they default on a single payment, buyers forfeit their right to the property, with no equity. In many cases, prospective buyers of these homes are not aware of the terms under which they enter into such contracts, and Harbour has come under scrutiny in many locations for discriminatory lending practices.
Our task is to analyze property, demographic, and sales data for Harbour properties; visualize our findings through maps and an interactive web application; and, as appropriate, support the claim of discrimination for legal proceedings. We will trace the chain of ownership of Harbour homes over time, search for correlations between property locations and demographics, and create tools for Atlanta Legal Aid to more easily access the information they need.
We are also working on another project related to housing justice: Atlanta’s anti-displacement tax fund program. As neighborhood revitalization occurs in Atlanta’s Westside, there are concerns that longtime residents will be displaced as the area gentrifies. One proposed measure to decrease this turnover is the anti-displacement tax fund, which will offset the increase in property taxes for eligible residents. We will analyze these eligibility requirements to determine how many people qualify for the program, and think about ways in which this program or other anti-displacement measures could be expanded. We hope that the data analysis and tools we build will increase understanding of these two important housing justice issues.
Cycle Atlanta: Seeing Like a Bike
Seeing Like a Bike is a project under direction of Christopher A. Le Dantec, an Associate Professor of Digital Media in the School of Literature, Media, and Communication at Georgia Tech. The main purpose of this project is to identify environmental factors that affect the level of bike rider stress. During this summer, four students from different universities are working on the development of the bike-based sensor platform which will allows us to see what the bike sees. By the end of this term, we will have a small number of bikes mounting sensor array able to collect data to start to building predictable models of cycling stress base on environmental factors.
Building Energy Analytics
All Georgia Tech buildings have sensors which have been assessing how much energy is being used every 15 minutes for the past few years. Although a lot of data has been collected, for the most part, it has remained unutilized. As a result, our goal is to use that data, along with other external data like local weather and building occupancy, in order to model energy usage at Georgia Tech. In doing so, we hope to both determine which factors contribute to energy usage and target buildings that are most inefficient and in need of an upgrade.
UN Climate Challenge: Predicting & Alleviating Road Flooding in Senegal
Climate change will exacerbate existing socioeconomic vulnerabilities and threaten the success of crucial development schemes. Developing and maintaining resilient road networks is essential for meeting several UN sustainable development goals. However, currently about 75% of the road network in Africa is unpaved, making it especially susceptible to damage from precipitation.
As a result, our goal is twofold. One, we want to assess the effects of flooding events on road network connectivity in Senegal by determining which roads are most susceptible to flooding based on weather and topographical data. Two, we want to make recommendations for maintenance and upgrades that will enhance the climate resilience of the road network. We will do this by determining the volume of traffic of each road to quantify its contribution to accessibility between different parts of the countries, and perform a budget-constrained optimization framework to find a set of roads to target for improvements.