Exploring network properties of social media interactions and activities during Hurricane Sandy

In this study, we analyze Twitter data to understand information spreading activities of social media users during Hurricane Sandy. We create multiple subgraphs of Twitter users based on activity levels and analyze such network properties. We observe that user information sharing activity follows a power-law distribution suggesting the existence of few highly active nodes in disseminating information compared to many other nodes. We also observe close enough connected components and isolates at all levels of activity, and networks become less transitive, but more assortative for larger subgraphs. We also analyze the association between user activities and characteristics that may influence user behavior to spread information during a crisis. Users who are centrally placed in the network, less eccentric and have higher degrees, they are more active in spreading information. Our analyses provide insights on how to exploit user characteristics and network properties to spread targeted information in major disasters.

Abstract licence: CC BY-NC

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