Abstract
Agricultural and environmental economists frequently use content analysis of textual data to gain a deeper understanding of public discourses that reflect the conflicting interests and attitudes of various stakeholders with regard to agricultural issues. These discourses encompass topics such as nitrogen leaching, climate change, biodiversity loss, and animal welfare. However, the procedural standards of content analysis established in communication studies are rarely fully adhered to due to a lack of interdisciplinary communication. This paper provides applied agricultural economists with a conceptual background to systematic search term validation to facilitate the transparent generation of high-quality databases for the content analysis of large datasets.
| Original language | English |
|---|---|
| Article number | qoaf012 |
| Journal | Q Open |
| Volume | 5 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Austrian Fields of Science 2012
- 405002 Agricultural economics
- 508007 Communication science
Keywords
- gemini
- search terms
- animal welfare
- content analysis
- chatgpt
- artificial intelligence
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