Eggs: social and online media-derived perceptions of egg-laying hen housing

• Published in: Poultry science 2020-11, Vol.99 (11), p.5697-5706
• Main Authors: Widmar, Nicole, Bir, Courtney, Wolf, Christopher, Lai, John, Liu, Yangxuan
• Format: Article
• Language: English
• Subjects: Animal Husbandry - statistics & numerical data; Animal Welfare - statistics & numerical data; Animals; big data; Chickens; Community Participation - statistics & numerical data; consumer demand; consumer perceptions; egg production; Eggs; Female; Housing, Animal - standards; Housing, Animal - statistics & numerical data; Humans; Internet; Metabolism and Nutrition; Perception; Social Media; social media analytics
• ISSN: 0032-5791; 1525-3171
• DOI: 10.1016/j.psj.2020.07.011

Enormous quantities of data are generated through social and online media in the era of Web 2.0. Understanding consumer perceptions or demand efficiently and cost effectively remains a focus for economists, retailer/consumer sciences, and production industries. Most of the efforts to understand demand for food products rely on reports of past market performance along with survey data. Given the movement of content-generation online to lay users via social media, the potential to capture market-influencing shifts in sentiment exists in online data. This analysis presents a novel approach to studying consumer perceptions of production system attributes using eggs and laying hen housing, which have received significant attention in recent years. The housing systems cage-free and free-range had the greatest number of online hits in the searches conducted, compared with the other laying hen housing types. Less online discussion surrounded enriched cages, which were found by other methods/researchers to meet many key consumer preferences. These results, in conjunction with insights into net sentiment and words associated with different laying hen housing in online and social media, exemplify how social media listening may complement traditional methods to inform decision-makers regarding agribusiness marketing, food systems, management, and regulation. Employing web-derived data for decision-making within agrifood firms offers the opportunity for actionable insights tailored to individual businesses or products.