Modeling the Decision to Allow Hydraulic Fracturing

In this study we will determine how computer science data mining principles can aid researchers in the creation of ethnographic decision models. Our approach uses these principles to determine which decision attributes will be most useful for predicting whether homeowners will lease land for hydraulic fracturing. Hydraulic fracturing (or fracking) is a controversial process of extracting natural gas where millions of gallons of chemicals and water are pumped into the ground to fracture rock and release the gas for collection. There are potential health risks and economic benefits for homeowners. We identify a number of possible attributes that affect this decision, such as financial situation, and prevalence of fracking in the local community. Data will be collected from 50 landowners who have been approached about leasing their land for fracking. We will conduct interviews and surveys, model this decision process, and compare the model to actual outcomes. Our goal is to use computer science data mining techniques to identify which attributes have the most influence on this difficult decision.