Exploring network properties of social media interactions and activities during Hurricane Sandy
Exploring network properties of social media interactions and activities during Hurricane Sandy
复制标题
DOI：
10.1016/j.trip.2020.100143
复制
发表时间：
2020-07
影响因子：
--
通讯作者：
Sandy;A. M. Sadri;Samiul Hasan;S. Ukkusuri;Manuel Cebrian
中科院分区：
文献类型：
--
作者：
Sandy;A. M. Sadri;Samiul Hasan;S. Ukkusuri;Manuel Cebrian
在这项研究中，我们分析了Twitter数据，以了解飓风桑迪期间社交媒体用户的信息传播活动。我们根据活动水平创建Twitter用户的多个子图，并分析这些网络属性。我们观察到，用户信息共享活动遵循幂律分布，这表明存在一些高度活跃的节点相比，许多其他节点在传播信息。我们还观察到足够接近的连接组件和隔离在所有级别的活动，网络变得不那么可传递，但更大的子图的可预测性。我们还分析了用户活动和可能影响用户行为的特征之间的关联，以在危机期间传播信息。在网络中处于中心位置的用户，不那么古怪，有更高的学位，他们在传播信息方面更活跃。我们的分析为如何利用用户特征和网络属性在重大灾害中传播有针对性的信息提供了见解。
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.