Fetching datasets…
We use essential cookies to keep you signed in and improve your experience. Cookie Policy
Engineering deep-dives, research findings, and product updates from the team.
How we engineered a distributed collection system that continuously archives public conversations across 100+ platforms — from Reddit and YouTube to Mastodon and Bluesky.
Heshan Sanjuka
June 28, 2026
Our heuristic rule engine now delivers 80+ enrichment fields at sub-millisecond per post — with zero API costs and 100% determinism. Here is why we made the switch and what we learned.
June 22, 2026
An analysis of current trends in social media dataset availability, quality challenges, and what researchers and developers need to know before building their next model.
June 15, 2026
Bot detection on Mastodon, Bluesky, and the fediverse presents unique challenges. We built a cross-platform behavioral analysis system — here is how it works and what we found.
June 8, 2026
Our new financial signal detection pipeline identifies market-relevant events — earnings chatter, regulatory news, whale movements, and more — across social media in near real-time.
June 1, 2026
Sentiment analysis varies wildly across platforms. A 4chan post and a LinkedIn article require fundamentally different approaches. Here is our framework for platform-aware sentiment analysis.
June 5, 2026
Social media data is one of the richest sources for fine-tuning large language models. Here is our complete workflow for curating, enriching, and preparing social datasets for LLM training.
July 5, 2026
Collecting public social media data at scale requires careful attention to privacy regulations. Here is how we approach GDPR, CCPA, and platform-specific compliance in our pipeline.
July 1, 2026
Extracting people, organizations, products, and events from social media streams requires more than off-the-shelf NER. Here is our approach to high-recall entity extraction at scale.
June 27, 2026
Every platform produces data differently. Our quality scoring system evaluates completeness, reliability, and signal strength across heterogeneous sources. Here is how it works.
Social media is often the first place events are reported — before news outlets, before official channels. Here is how to build an event detection system from social data streams.
June 17, 2026
Every social media platform is a unique engineering challenge. From Reddit API quirks to 4chan board dynamics, here are the hard-won lessons from building collectors for 100+ platforms.
June 12, 2026
Crypto markets are driven by social sentiment more than traditional finance. But not all sentiment signals are equal. Here is how to extract actionable signals from social media noise.
June 7, 2026
Most social media dashboards show vanity metrics. Here is how to build one that surfaces actionable signals for research, brand monitoring, and market intelligence.
June 2, 2026
Social media data reflects the biases of its creators and platforms. Without careful debiasing, your AI model will inherit and amplify those biases. Here is our framework for producing fairer training data.
June 4, 2026
Choosing the right dataset format can save weeks of preprocessing. Here is a practical comparison of common formats, schema designs, and tradeoffs for social media AI training datasets.
June 10, 2026
Get notified when new posts are published. Manage in settings.
