Summary
This study employs a dual-method approach—farmer survey and web-scraping with Natural Language Processing—to characterise sentiment and perceived challenges in pastured and integrated poultry production. Both farmers and online stakeholders identified soil health, animal welfare, and weed control as key benefits; however, farmers emphasised regulatory and processing barriers whilst these topics were largely absent from online discourse. The parallel analysis reveals substantive differences between farmer experience and public/stakeholder perception, suggesting that niche agricultural systems benefit from multi-stakeholder sentiment assessment rather than single-source evaluation.
Regional applicability
The study was conducted in the United States and reflects US regulatory, market, and farming contexts. Whilst the methodological approach (combined survey and NLP-based sentiment analysis) is transferable to United Kingdom poultry and mixed farming systems, the specific regulatory barriers, processing infrastructure, and online discourse patterns identified are US-specific and may not directly apply to UK PIPP adoption, where certification schemes, water protection policies, and feed supply chains differ materially.
Key measures
Sentiment analysis of farmer survey responses (n=53 producers); thematic coding of 2,399 online posts from 1,089 unique authors; longitudinal comparison of topics mentioned across both data sources (2019–2021)
Outcomes reported
The study compared farmer survey responses (n=53) with 2,399 web-scraped online posts (2019–2021) to identify perceived benefits, barriers, and challenges associated with pastured and integrated poultry production (PIPP). Both data sources highlighted soil health, animal welfare, and weed control as benefits, whilst identifying distinct gaps between farmer and online stakeholder perspectives on regulatory, processing, and mental health concerns.
Topic tags
Dig deeper with Pulse AI.
Ask about this record, its theme or its relevance to UK farming and policy. Pulse AI uses selected catalogue evidence and cites the sources it draws on.