Deriving Population Assessment through Opinion Polls, Text Analytics, and Agent-Based Modeling
Surveys are an important tool for measuring public opinion, but they take time to field, and thus may quickly become out of date. Social and news media can provide a more real-time measure of opinions but may not be representative. We describe a method for combining the precision of surveys with the timeliness of media using an agent-based simulation model to improve real-time opinion tracking and forecasting. Events extracted through text analytics of Afghan media sources were used to perturb a simulation of representative agents that were initialized using a population survey taken in 2005. We examine opinions toward the U.S., the Afghan government, Hamid Karzai, and the Taliban, and evaluate the model’s performance using a second survey conducted in 2006. The simulation results demonstrated significant improvement over relying on the 2005 survey alone, and performed well in capturing the actual changes in opinion found in the 2006 data.
KeywordsPopulation assessment agent-based modeling public opinion polls text analytics social identity theory
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