Introduction: Cancer imposes emotional, financial, and decision-making burdens on pet owners. This study used social media listening (SML) and natural language processing (NLP) to examine owner experiences of canine cancer care, focusing on treatment decisions, specialist referral barriers, and roles of emotion, communication, cost, and quality of life (QoL).

Materials & Methods: Public posts about canine oncology were collected en masse using Pulsar Platform™ from Reddit, X (Twitter), blogs, forums, and other platforms spanning two years of online content. Posts were cleaned by de-duplication, advertisement and emoji replacement and filtered for relevance, and to isolate pet owner perspectives rather than veterinary professionals, using zero-shot large language model classification (precision >98%). The corpus was analysed using sentiment and emotion analysis, thematic extraction, and non-negative matrix factorization topic modelling, including cost-related and referral-related subsets.

Results: From 28,784 initial posts, 11,878 relevant posts were retained. X contributed 74%, Reddit 10%, and forums 8%. Most posts expressed negative sentiment (66%) and sadness (64%). Six themes emerged: emotional support, treatment navigation, financial strain, education and advocacy, cultural resonance, and end-of-life decision-making. Cost-related posts (n=2,008) highlighted affordability concerns, insurance limitations, and fundraising. Referral-related posts (n=341) emphasized delays, diagnostic uncertainty, communication gaps, and access barriers. Topic modelling revealed QoL as a central construct guiding treatment and end-of-life decisions.

Conclusions: Online posts demonstrated owner frustration centred on referral delays, unclear general practice–specialist pathways, and financial uncertainty. Early expectation-setting, clear shared-care communication, and cost transparency may reduce referral friction and enhance owner experience in veterinary oncology.