Adaptive Information Extraction from Social Media for Actionable Inferences in Public Health

We are sorry, this position has been filled.

Social media is a major source of non-curated, user-generated feedback on virtually all products and services. Users increasingly rely on social media to disclose serious real-life incidents, such as a food poisoning incident at a restaurant, rather than reporting to official government channels. This research position will focus on cross-lingual analysis of social media content to support our lab's ongoing collaboration with the New York City Department of Health and Mental Hygiene and the Los Angeles County Department of Public Health.

Lab: InfoLab

Direct Supervisor: Luis Gravano

Position Dates: 6/1/2020 - 8/21/2020

Hours per Week: 40

Paid Position: Yes

Credit: Yes

Number of positions: 1

Qualifications: Machine Learning, Natural Language Processing, Databases

Eligibility: Sophomore, Junior, Senior (SEAS only)

Luis Gravano, [email protected]