A Twitter Data Credibility Schema Framework - Hurricane Harvey as a Use Case

Authors: Jingchao Yang*, George Mason University, Manzhu Yu, George Mason University, Han Qin, Ankura Consulting Group, Mingyue Lu, Nanjing University of Information Engineering, Chaowei Yang, George Mason University
Topics: Geographic Information Science and Systems, Spatial Analysis & Modeling
Keywords: Social Media, Credibility
Session Type: Paper
Day: 4/5/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Washington 6, Marriott, Exhibition Level
Presentation File: No File Uploaded

Social media data have been used to improve geographic situation awareness in the past decade. Although it has free and openly availability advantages, only a small proportion is related to situation awareness, and reliability or trustworthiness is a challenge. A credibility framework is proposed for Twitter data in the context of disaster situation awareness. The framework is derived from crowdsourcing which states that errors propagated in volunteered information decrease as the number of contributors increases. In the proposed framework credibility is hierarchically assessed on two tweet levels. The framework is tested using Hurricane Harvey Twitter data in which situation awareness related tweets are extracted using a set of predefined keywords including power, shelter, damage, casualty, and flood. For each tweet text messages and associated URLs are integrated to enhance the information completeness. Events are identified by aggregating tweets based on their topics and spatiotemporal characteristics. Credibility for events is calculated and analyzed against the spatial, temporal, and social impacting scales. This framework has the potential to calculate the evolving credibility in real time, providing users insight on the most important and trustworthy events.

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