#GoingtotheFair: a social media listening analysis of agricultural fairs1. Issue 3 (20th July 2020)

• Record Type: Journal Article
• Authors: Mahoney, Julie A; Widmar, Nicole J O; Bir, Courtney L
• Is Part Of: Translational animal science. Volume 4:Issue 3(2020)
• Publication Date: 2020-07-20
• Subjects: agricultural fair -- fairs -- livestock -- online media sentiment -- zoonotic disease; Livestock -- Periodicals; Livestock; Periodicals; 636.005
• DOI: 10.1093/tas/txaa139
• Languages: English
• ISSNs: 2573-2102

Abstract

Abstract: Agricultural fairs provide one of the last frontiers, and largest stages, for showcasing livestock agriculture to the public. However, public funding, attendance revenue, animal biosecurity, and public health concerns are all aspects worthy of conversation and increased research attention given the interaction between livestock animals and the general public in fair and festival settings. A prominent social media listening and data analytics platform was used to quantify online and social media chatter concerning agricultural fairs during a 27-mo period. A general search for online media referencing agricultural fair keywords was designed; social and online media mentions of agricultural fairs ( n = 2, 091, 350 mentions) were further queried according to their reference to livestock, fair food, or the major agricultural product producing species of dairy and beef cattle ( n = 68, 900), poultry ( n = 39, 600), and swine ( n = 31, 250). Numbers of search results were found to be seasonal and Twitter was the single largest domain for all fair-related results; in contrast, the majority of livestock-related media was generated by news sources rather than from Twitter. On a weekly basis, the percentage of fair livestock mentions with species-specific reference was highly variable ranging from 0% to 86.8% for cattle, 0% to 85.7% for poultry, and 0% to 76.9% for swine. In addition to quantifying total search hits or mentions, the positivity/negativity of the search results was analyzed using natural language processing capabilities. The net sentiment quantified is the total percentage of positive posts minus the percentage of negative posts, which results in a necessarily bounded net sentiment between −100% and +100%. Overall net sentiment associated with mentions of agricultural fairs was positive; the topics garnering the highest positive sentiments were fair food and cattle (both 98% positive). Online discussion pertaining to agricultural fairs and swine was overall positive despite references to swine flu outbreaks. In conclusion, livestock and animal products had positive net sentiment over the time period studied, but there are multiple aspects of agricultural fairs worthy of further investigation and continued vigilance, including zoonotic disease risk and public perceptions of livestock industries.