- Turning online conversations into insights that improve veterinary care
Our Mission
Pet owners share their experiences, concerns, and questions online every day. From Facebook groups to X threads, these conversations hold valuable clues about unmet needs in veterinary care, emerging health trends, and owner perceptions and pain points. By tapping into these digital discussions, we can better understand what matters most to companion animal owners, and improve care accordingly.
Under the leadership of Prof. Kevin Wells, the DataHub team have become experts in Social Media Listening (SML) for veterinary medicine. Using advanced AI techniques we collect posts from diverse platforms, identify patterns and themes, and extract insights that inform research and practice.
What we're doing
Our methodology combines Non-Negative Matrix Factorisation (NMF) to uncover key themes and clusters of discussion, and Large Language Models (LLMs) to contextualise and interpret these themes with nuance. This powerful combination turns raw social media data into meaningful insights. In one study, we analyse five years of social media posts to explore:
Pet Pain management concerns
Owners frequently express uncertainty about recognising pain in their pets and managing it effectively
broader trends in veterinary care
Growing interest in preventative care, holistic treatment and advanced diagnostics
Owner expectations and frustrations
Frustrations surround cost, accessibility, and transparency in veterinary services
Why our work matters
- Real-Time Feedback
- Understanding what pet owners care about today
- Trend Detection
- Spotting emerging issues before they become widespread
- Evidence-Based Decision
- Informing research and clinical practice with real-world data
Help us harness the power of digital conversations to improve animal health. Explore our research, share our story, and help us make an impact
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