SnapSim Methodology

Danielle, Edwin, Harihar, Tami

Our project goal was to make our audience feel empathy for families on SNAP who must make sacrifices when shopping. We implemented this goal by creating an interactive text-based narrative.

Our first prototype was a game that utilized food price data from the Market Basket circular over 10 weeks. The dataset presents the data as scanned images, so we manually transcribed the items and prices. It also used nutrition information from the National Nutrient Database and restaurant websites (ex. McDonalds). In the game, the player aimed to buy a healthy week of food while staying under budget. However, we found that the addition of nutrition data did not help foster empathy (based on responses to our post-game survey), so we omitted nutrition in our final project.

For our next iteration, we learned about other connections people have to food and used that to tell a story to evoke empathy. To understand the demographics of SNAP families, we studied the examined the income data and SNAP benefit data from the the Food Environment Atlas and read the “Characteristics of SNAP Households” report from the USDA. To understand people’s connection to food, we created a survey and received about 20 responses from friends. These responses illustrated some reasons that people eat the foods that they do.

With that, we moved from a game structure to an interactive narrative. Rather than using data to evoke empathy, we chose to use stories. We built a character fitting the demographic data and we created stories around food which captured some of the connections we observed in our survey responses. To determine the character’s budget, we used income and monthly SNAP benefit data from the USDA Food Environment Atlas. We supported our numbers by looking up salaries on the Bureau of Labor Statistics and using a SNAP benefit calculator.

We aimed to conclude the narrative by connecting it back to reality. To do this, we created a map indicating SNAP participation rates (hoping that a user’s connection to their state or country would help them identify with the data) and the locations of food banks around the country (as a call to action). Getting data on food bank locations was very time consuming. We fetched HTML from Feeding America and wrote a Python script to clean it. We then used Google’s geocoding service to convert the addresses to latitudes and longitudes.

We had four total iterations of our interactive narrative – each had a different user experience. The changes were guided by questionnaires given to our testers and feedback from games expert Prof. Sara Zaidan.

Our final product is an interactive text-based narrative. The player is a single mother grocery shopping for herself and her two children. Each food item has a story indicating its importance to the family. In order to stay within budget, the player must forgo buying some of the foods. At the end, we show the player a map of SNAP participation around the country to illustrate that for some families, this game may be a reality. The map also displays food banks (and links to their websites), encouraging the user to act on their empathy by donating or volunteering.

We created two variants of our project: one focusing on removing items to the grocery cart, and the other focusing on adding items to the grocery cart.

We have a number of repositories for our project:


first prototype

second prototype

final project (variant 1)

final project (variant 2)

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