Analyzing the spread of tweets in response to Paris attacks

Twitter is a widely used social media platform that provides a rich source of geotagged posts along with extended content information, such as hashtags or images. Since tweets are frequently used for the instant sharing of news, thoughts, and ideas, they reflect to some extent the effects of critical events, such as natural disasters or political riots, on the society, and how the society perceives such events. This paper analyzes, using exploratory methods and regression models, the spatio-temporal patterns of geo-located tweets that were posted in response to the November 2015 Paris terrorist attacks. It determines how information about this event spread around the world in the Twitter network and assesses how content category, tweet format, and profession of the user influence tweet popularity, measured by the number of retweets. The paper contributes to a better understanding of how the Twitter community reacts to unexpected events and how information about such an event propagates geographically. •Analysis of the spatial patterns of retweets, which extends previous work that focused on non-spatial retweet patterns.•Spatiotemporal regression model for the prediction of counts of tweets around the world, identifying hierarchical spread.•Analysis of the influence of tweet content category, tweet format, and user profession on the number of retweets.