Exploring the Limitations of Traditional Public Policy Analysis and the Potential of Big Data: A Case Study of Social Media Discourse on the Renewable Fuel Standard

Courtney Breckenridge and Nicholas Guehlstorf ()
Additional contact information
Courtney Breckenridge: Southern Illinois University Carbondale
Nicholas Guehlstorf: Southern Illinois University Edwardsville

Chapter Chapter 5 in Environmental Policy Science’s Exploration for Innovative Data, 2025, pp 69-88 from Springer

Abstract: Abstract Using the U.S. Renewable Fuel Standard (RFS) as a case study, this chapter contrasts the growing potential of big data research methodologies with the limitations of conventional policy analysis methods. Established via amendments to the Clean Air Act in the early 2000s, the RFS was designed to increase U.S. energy independence and reduce greenhouse gas emissions caused by the combustion of transportation fuels. More than 20 years later, the RFS remains the subject of significant discourse and debate amongst legislators, federal agencies, and stakeholder groups. Through an analysis of RFS-related social media posts and associated metadata collected from Twitter (now known as “X”), the authors utilize machine learning and content analysis to assess public discourse and stakeholder perspectives. The research explores the intersection of policy, politics, and public sentiment using the Multiple Streams Framework to reveal the complexities of advocacy, opposition, and the framing of the RFS in public debates. The results provide support for both the significance of machine learning methods and the relevance of Multiple Streams as a theoretical framework. Legislator advocacy or opposition is strongly correlated with the characteristics of their district, reflecting the interests and livelihoods of the voters who elect them to office.

Date: 2025
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nrmchp:978-3-031-90889-7_5

Ordering information: This item can be ordered from
http://www.springer.com/9783031908897

DOI: 10.1007/978-3-031-90889-7_5

Access Statistics for this chapter

More chapters in Natural Resource Management and Policy from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().