论文标题
表征COVID-19大流行期间Twitter中信息领导者的表征
Characterizing information leaders in Twitter during COVID-19 Pandemic
论文作者
论文摘要
信息是危机期间的关键，例如当前的共同-19大流行所产生的信息，因为它极大地塑造了人们的意见，行为及其心理学。误导性的不言语是与大流行有关的重要继发危机。 fodemics可以在不同方面扩大大流行的真正负面后果：社会，经济甚至卫生。例如，非洲人群可能导致人口群体之间的仇恨，使社会影响其反应或导致负面习惯有助于大流行传播。相反，可靠和信任的信息以及希望和团结的信息可用于控制大流行，建立安全网并有助于促进弹性。我们根据对从该社交网络中的活动得出的社会图表的分析，为在Twitter中表征领导者的框架的基础。中心度指标用于将网络拓扑和节点的拓扑表征为潜在的领导者。将这些指标与Twitter管理的用户流行度指标进行了比较。然后，我们在视觉上评估领导者群的拓扑。我们建议该工具成为系统检测和授权用户对网络集体行为和信息传播具有积极影响的用户的基础。
Information is key during a crisis such as the one produced by the current COVID-19 pandemic as it greatly shapes people opinion, behavior and their psychology. Infodemic of misinformation is an important secondary crisis associated to the pandemic. Infodemics can amplify the real negative consequences of the pandemic in different dimensions: social, economic and even sanitary. For instance, infodemics can lead to hatred between population groups that fragment the society influencing its response or result in negative habits that help the pandemic propagate. On the contrary, reliable and trustful information along with messages of hope and solidarity can be used to control the pandemic, build safety nets and help promote resilience. We propose the foundation of a framework to characterize leaders in Twitter based on the analysis of the social graph derived from the activity in this social network. Centrality metrics are used to characterize the topology of the network and the nodes as potential leaders. These metrics are compared with the user popularity metrics managed by Twitter. We then assess the resulting topology of clusters of leaders visually. We propose this tool to be the basis for a system to detect and empower users with a positive influence in the collective behavior of the network and the propagation of information.
