Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/325687 
Year of Publication: 
2024
Citation: 
[Journal:] Italian Review of Agricultural Economics (REA) [ISSN:] 2281-1559 [Volume:] 79 [Issue:] 2 [Year:] 2024 [Pages:] 93-106
Publisher: 
Firenze University Press, Florence
Abstract: 
Starting in January 2024, street protests by farmers' groups spread in several European countries. The demands, which started from rather specific aspects, have broadened to involve economic, environmental and geo-political considerations, calling the already weakened European Green Deal even more into question. Starting from an analysis of the motivations for the protests and the responses provided by national governments and European institutions, the article tracks the main arguments that characterized the motivations of the so-called 'tractor protests', through the methodology of Sentiment Analysis applied to the social network of accounts (specifically, X) relating to different categories of subjects interested in the debate. The results indicate a generally positive sentiment, characterised by trust and anticipation, suggesting potential for improving the relationship between society, institutions, and the conditions of farmers. Farmers remain at the centre of the debate, which focused on two key areas: the economic and competitive conditions of agricultural businesses, and the compatibility and economic sustainability of the environmental regulations embedded in European policies. The research revealed that the demands were somewhat fragmented and inconsistent. Nevertheless, the protests, although short-lived, had a significant impact by prompting European institutions to steer environmental and agricultural policies in new directions. Additionally, the research highlights that innovative investigative methods can be effectively applied to examine the interplay between the technicalities of public policies and collective perceptions.
Subjects: 
agriculture
European Union
farmers' protests
Italy
sentiment analysis
social media
JEL: 
Q18
Q17
O13
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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