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#Eggs: social and online media-derived perceptions of egg-laying hen housing
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 dema...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647710/ https://www.ncbi.nlm.nih.gov/pubmed/33142487 http://dx.doi.org/10.1016/j.psj.2020.07.011 |
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author | Widmar, Nicole Bir, Courtney Wolf, Christopher Lai, John Liu, Yangxuan |
author_facet | Widmar, Nicole Bir, Courtney Wolf, Christopher Lai, John Liu, Yangxuan |
author_sort | Widmar, Nicole |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7647710 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-76477102020-11-13 #Eggs: social and online media-derived perceptions of egg-laying hen housing Widmar, Nicole Bir, Courtney Wolf, Christopher Lai, John Liu, Yangxuan Poult Sci Metabolism and Nutrition 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. Elsevier 2020-08-06 /pmc/articles/PMC7647710/ /pubmed/33142487 http://dx.doi.org/10.1016/j.psj.2020.07.011 Text en © 2020 Published by Elsevier Inc. on behalf of Poultry Science Association Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Metabolism and Nutrition Widmar, Nicole Bir, Courtney Wolf, Christopher Lai, John Liu, Yangxuan #Eggs: social and online media-derived perceptions of egg-laying hen housing |
title | #Eggs: social and online media-derived perceptions of egg-laying hen housing |
title_full | #Eggs: social and online media-derived perceptions of egg-laying hen housing |
title_fullStr | #Eggs: social and online media-derived perceptions of egg-laying hen housing |
title_full_unstemmed | #Eggs: social and online media-derived perceptions of egg-laying hen housing |
title_short | #Eggs: social and online media-derived perceptions of egg-laying hen housing |
title_sort | #eggs: social and online media-derived perceptions of egg-laying hen housing |
topic | Metabolism and Nutrition |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7647710/ https://www.ncbi.nlm.nih.gov/pubmed/33142487 http://dx.doi.org/10.1016/j.psj.2020.07.011 |
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