Welfare of animals significantly depends on how stakeholders perceive their needs and behave in a way to favor production systems that promote better welfare outcomes. This study aimed at investigating stakeholders' perception of the welfare of equines, small ruminants, and turkeys using text mining analysis. A survey composed by open-ended questions referring to different aspects of animal welfare was carried out. Text mining analysis was performed. A total of 270 surveys were filled out (horses = 122, sheep = 81, goats = 36, turkeys = 18, donkeys = 13). The respondents (41% veterinarians) came from 32 different countries. To describe welfare requirements, the words "feeding" and "water" were the most frequently used in all the species, meaning that respondents considered the welfare principle "good feeding" as the most relevant. The word "environment" was considered particularly important for turkeys, as well as the word "dry", never mentioned for other species. Horses stakeholders also considered "exercise" and "proper training" important. Goat stakeholders' concerns are often expressed by the word "space", probably because goats are often intensively managed in industrialized countries. Although the sample was too small to be representative, text mining analysis seems to be a promising method to investigate stakeholders' perception of animal welfare, as it emphasizes their real perception, without the constraints deriving by close-ended questions.
Text Mining Analysis to Evaluate Stakeholders' Perception Regarding Welfare of Equines, Small Ruminants, and Turkeys / E. Dalla Costa, V. Tranquillo, F. Dai, M. Minero, M. Battini, S. Mattiello, S. Barbieri, V. Ferrante, L. Ferrari, A. Zanella, E. Canali. - In: ANIMALS. - ISSN 2076-2615. - 9:5(2019 May 08), pp. 225.1-225.14.
|Titolo:||Text Mining Analysis to Evaluate Stakeholders' Perception Regarding Welfare of Equines, Small Ruminants, and Turkeys|
|Parole Chiave:||animal welfare; donkey; goat; horse; sheep; stakeholder perception; text mining; turkey|
|Settore Scientifico Disciplinare:||Settore AGR/19 - Zootecnica Speciale|
|Data di pubblicazione:||8-mag-2019|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.3390/ani9050225|
|Appare nelle tipologie:||01 - Articolo su periodico|