Research at Twitter Cortex
Applied Machine Learning Research to fuel the public conversation

Areas of Research
The Applied Research teams at Twitter Cortex focus on eight key areas of exploration: Content Understanding, Learning Methods, Recommender Systems, User Modeling, Machine Learning Ethics, HITL, Graph Learning, ML Ethics and Transparency Research, and Data Science.
Learning Methods
Leveraging new machine learning paradigms such as self-supervised learning and graph learning within our products, and generally improving how we do machine learning.
Human-In-The-Loop
Twitter data is public by design. HITL is an inherent part of the product lifecycle, decision-making, policy, and user research.
Data Science
Twitter Data Science embraces a culture of innovation in how we utilize the rich data from our platform, resulting in a direct impact on our core company objectives.