Abstract
Objectives
Social media are seldom explored in animal health despite the potential for insights into pet owners’ perceptions. Owners often seek information and advice online before seeking veterinary care. The aim was to investigate owners’ perceptions of feline allergic skin disease using Social Asset, a proof-of-concept social listening (SL) platform to create a dataset concerning information-seeking behaviours.
Methods
Fifty sources were searched for keywords related to feline pruritis. Bespoke topic filters were used to match content mentioning body areas, behaviours, symptoms, disease, solutions and treatment. Posts combining these terms were reviewed manually and marked as relevant if the post was: from an owner, identified an itchy cat, and not duplicated.
Results
30947 posts published from 2017- 2022 were filtered, 1346 unique items were reviewed and 309 were marked relevant. Internet forums (892/1346) and Twitter streams (362/1346) were the most likely sources of relevant posts: Reddit (98/309), Catsite (78/309), Twitter (73/309) and Quora (40/309). Relevant posts were most frequently from the United States (133/309), United Kingdom (10/309), Canada (4/309), Greece (4/309) and Australia (3/309). A single post came from each of 10 countries and 145/309 posts had no location. Text clustering analysis was conducted using Deeptalk.ai: “scratch” was the most frequent keyword (72/309).
Conclusions
SL provides unique insights into owner perceptions on health and veterinary care. Results showed that in these data, “scratch” was the most efficient term to identify relevant posts. The dataset could be strengthened by increasing keyword specificity and reducing “noise” using machine learning. It could enable data-driven decisions such as assessing demand for veterinary services by location, investigating disease risk factors and impact on quality of life. These findings will be validated by comparison with a direct pet owner survey and potentially veterinary practice data.