BD.20.007 – Modeling and simulation of public communication during a pandemic crisis from social media data

With the rapid growth of social media, a great number of people use online social media to communicate and share their opinion (e.g. about 2.8 million users in the Netherlands are using Twitter in 2019). This makes social media a valuable resource for tracking public opinion and analysing the communication among citizens. However, such communication can be very complex and public opinion can be misled through dynamic communication among social media users. These problems might be magnified when facing unexpected pandemic crisis like COVID-19, as fear and anxiety due to the pandemic will introduce negative opinions or misinformation.

Motivated by this, we propose to identify the dynamic mechanisms of public communication during a pandemic crisis and to generate insights to prevent the diffusion of negative opinion. This is done by analysing social media data collected during the COVID-19 crisis. We aim not only to build a social network structure to model the communication between social media users, but also to develop a simulation model for interpreting the communication behaviors.

Keywords

Big Data, simulation, social media