Geographic variability of Twitter usage characteristics during disaster events

Abstract

Twitter is a well-known microblogging platform for rapid diffusion of views, ideas, and information. During disasters, it has widely been used to communicate evacuation plans, distribute calls for help, and assist in damage assessment. The reliability of such information is very important for decision-making in a crisis situation, but also difficult to assess. There is little research so far on the transferability of quality assessment methods from one geographic region to another. The main contribution of this research is to study Twitter usage characteristics of users based in different geographic locations during disasters. We examine tweeting activity during two earthquakes in Italy and Myanmar. We compare the granularity of geographic references used, user profile characteristics that are related to credibility, and the performance of Naïve Bayes models for classifying Tweets when used on data from a different region than the one used to train the model. Our results show similar geographic granularity for Myanmar and Italy earthquake events, but the Myanmar earthquake event has less information from locations nearby when compared to Italy. Additionally, there are significant and complex differences in user and usage characteristics, but a high performance for the Naïve Bayes classifier even when applied to data from a different geographic region. This research provides a basis for further research in credibility assessment of users reporting about disasters

Keywords

• Geographic feature granularity
• Volunteered Geographic Information (VGI)
• Naïve Bayes
• Twitter
• credibility
• Geonames