Tom Tom Founders Festival 2018

Social media offers a diverse and intermeshed landscape of creators and consumers that cuts across traditional archetypes of genre and stardom. Given the speed of evolution, fractured landscape of delivery platforms, and sheer breadth of choices, discovering emerging talent becomes a now-classic big-data classification problem against a broad but shallow signal. Access to data remains the primary challenge to effective feature engineering in this space, and therefore to identifying the next Justin Bieber, political star, or terrorist leader. A cascade of models and feedback loops can address this problem by first scoring against a weak but suitably general source of information, such as Twitter, and then leveraging this rough set to prioritize subsequent, more-focused data collection. Once the search space has been sufficiently reduced, a deep learning (embedding) model can feasibly employed for similarity search and general inference.