We are the Digital Trace team at the Media Technology and Democracy (McGill University). Our mission is simple but ambitious: to bridge Applied AI and Computational Social Science by building scalable infrastructure to collect, process, and analyze cross-platform social media data.
Our insights empower researchers, policymakers, and journalists to better understand how digital information shapes society.
Technical Power:
Infrastructure & Analytics
- 7 Major Platforms: Continuous data ingestion from X, Facebook, Instagram, TikTok, YouTube, Bluesky, and Telegram.
- 24/7 Automated Pipelines: Near Real-time (72 hours) crawling, indexing, embedding generation, and normalization.
- Applied AI: We support advanced natural language and network analytics, enabling large-scale understanding of information dynamics.
- Seed List: 5,366 tracked entities with comprehensive metadata
Applications & Research Highlights
- Federal Elections (2025): Showed that influencers, AI-made false content, and different groups using different platforms shaped the conversation and created emerging risks for public trust.
- Tenet Media (2024): Tracked how key influencers connected with Canadians online and who amplified their messages across platforms.
- Meta News Ban (2023): Used AI to examine 133,000 images from political groups and measure how the ban changed what people saw and shared.
- Ongoing Initiatives: Detecting coordinated campaigns; measuring where communities stand on issues; mapping political influencers; rapid-response incident analysis.
Stay tuned
This blog will share our technical insights, data architecture notes, and research updates. From pipeline optimization to AI research, we’ll be opening up how we make social media data actionable and transparent.
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