Abstract:

Empirical evidences indicate that the inter-event time distribution of human behavior exhibits heavy-tailed features. This paper studied the interest-driven human dynamics using data from Sina micro-blog, which is one of the most successful on-line social media systems in China. It chose three specific events and a period of time called “general situation” in which no big events occur. The results of data analysis showed that the inter-post, inter-comment and inter-forward time distributions of each of these events follow the power law distribution. Then this paper proposed an interest-driven model with the concept of batch customer arrival in the Queuing Theory. And this model well explains the relationship between the power-law exponent and the effective duration of each event. The findings are helpful for discovering regular patterns of the message dissemination.

Key words: human dynamics, micro-blog, power-law distribution, BA model, micro-blog user