Project Grant 2333538

Award Date 10/1/24
Completion Date 9/30/27
Dollars Obligated $323K
Federal Grant Program
47.075
Assistance Type
Project Grant
Place of Performance
Chicago, IL 60616, USA
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This $322,812 project grant, awarded by the National Science Foundation (NSF) under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), supports research to advance the understanding of how people engage with news online and how their behaviors evolve over time. The key products and services to be delivered include:

  1. Developing computational models to identify different types of news engagement behaviors and their progression stages, using advanced language and user modeling techniques.
  2. Establishing a technical framework to estimate causal relationships between various news engagement behaviors, combining natural language processing and causal inference methods.
  3. Testing socio-technical hypotheses regarding factors like strong issue positions, trust, and information reliability that influence news engagement behaviors.

The research will employ multi-year social media data enriched with political news source databases, evaluating models through machine learning metrics, synthetic experiments, and validation through surveys and focus groups. This comprehensive approach aims to produce more accurate predictive models and robust causal estimation methods applicable across domains to study human behavior from online data. The project will also integrate research findings into university courses and community workshops to foster a more informed public.

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