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Twitter Bot Detection Software for Disaster Relief Applications

This research seeks to detect Twitter bots that appear after disasters or other emergencies, which will prevent the spread of fake news and malicious content, make existing disaster relief systems more precise, and improve other disaster relief efforts on social media. The classification, using machine learning techniques, and removal of these bots will prevent human users from accidentally interacting with these bot accounts and being manipulated by them. In the future, a similar bot detection software could be used to identify bots in real-time inside the social media application that a human user is interacting with to improve relief efforts.

Symposium Participant

Portrait of Matthew Davis

Matthew Davis

Project Details

Symposium Date: Fall 2018

Research Theme: Security

Presentation Type: FURI

Faculty Mentors

  • Huan Liu