To arms: The battle against misinformation
Who is this presentation for?
- Product managers, concerned citizens, data scientists, and engineers
Danielle Deibler examines an approach to detecting bias, fine-grained emotional sentiment, and misinformation through the detection of political narratives in online media. As building blocks, the methodology uses human-in-the-loop, alongside other natural language processing and computational linguistics techniques, with examples focused on the 2020 US presidential election.
Danielle uses real-world examples of data-driven and active learning-derived analysis of data collected in conjunction with tracking of the 2020 US presidential election. She highlights both the successes and failures seen in over a year of work in the US political sphere. Her use cases focus on how messaging spreads, both negatively (propaganda) and positively (prodemocracy campaigns), the political bias of those on Twitter, and asymmetries in coverage of male versus female candidates.
- A basic understanding of human-in-the-loop learning and the US presidential race for 2020
What you'll learn
- Discover available techniques in natural language processing
Danielle Deibler is the cofounder and CEO of MarvelousAI, an early stage startup focused on building natural language technology to discover and expose propaganda, disinformation, and bias to enable advocates and policymakers to devise countermeasures and immunities. She has over 25 years’ experience in the internet infrastructure, security, networking, interactive technology, machine learning, and AI technologies. Her primary area of focus in the last 20 years has been building scalable real-time interactive platforms. Previously, she was CEO and cofounder of leading-edge regulatory technology startup Compliance.ai, founder of Apps54 and Ignited Artists, and an entrepreneur in residence at Trinity Ventures and held senior leadership positions in software development, engineering, business development, and product management for KIXEYE, Adobe, DIGEX, and UltraDNS.
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