A Human-Machine Collaborative System for Identifying Rumors on Twitter

The spread of rumors on social media, especially in time-sensitive situations such as real-world emergencies, can have harmful effects on individuals and society. In this work, we developed a human-machine collaborative system on Twitter for fast identification of rumors about real-world events. The system reduces the amount of information that users have to sift through in order to identify rumors about real-world events by several orders of magnitude.