Understanding Information Spreading in Social Media during Hurricane Sandy: User Activity and Network Properties

TL;DR

This study analyzes Twitter data during Hurricane Sandy to understand how user activity and network properties influence information dissemination, revealing key patterns and user characteristics that affect information spread during crises.

Contribution

It provides a detailed analysis of user activity patterns and network structures on Twitter during a disaster, highlighting factors that influence information dissemination.

Findings

User activity follows a power-law distribution.

Networks become less transitive and more assortative with size.

Active users are centrally located, less eccentric, and have higher degrees.

Abstract

Many people use social media to seek information during disasters while lacking access to traditional information sources. 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 network properties of the subgraphs. We observe that user information sharing activity follows a power-law distribution suggesting the existence of few highly active nodes in disseminating information and many other nodes being less active. 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 become more active in spreading information if they are centrally placed in the network, less eccentric, and have higher degrees. Our analysis provides insights on how to exploit user characteristics and network properties to spread information or limit the spreading of misinformation during a crisis event.