Measurements of the competitive characteristics of multi-topic propagation in online social networks

Online social networks have many topics but people's attention spans are very limited, so the many topics compete for the scarce user attention spans. This competitive relationship affects the propagation of information and the formation of public opinions. Most existing research has focused on the spread of individual topics. This study investigates the spread of multiple topics and methods to quantitatively describe the competitive characteristics. Topic and user level methods are developed to measure resource changes, topic competition intensity, user attention transitions and topic relevance. Metrics are developed for the resource variation rate and the user attention transition rate. Measurements of the actual data collected from Sina Weibo show that the total user attention level is almost stable with most user attention transitions moving from existing topics to newly appearing topics and between similar topics. These measurements provide modeling of the multi-topic propagation processes.