Measurement and analysis of topology and information propagation on Sina-Microblog

Abstract

Sina-Microblog, the earliest and biggest microblogging service in China, has become one of the most popular media in information propagation. In order to gain insights into the topological and information diffusing characteristics of microblogging network in China, we crawled Sina-Microblog for about 3 months and obtain the trace of its topology and topics. Compared with other online social networks, our measurement study shows a number of interesting findings. Our data suggests that Sina-Microblog network has apparent small-world effect and scale-free characteristic, specially, the outdegree distribution appears to have multiple separate power-law regimes with different exponents. We also observe the overlay graph of Sina-Microblog represents assortative mixing pattern and weak correlation of indegree and outdegree. Moreover, by constructing the cascades of different topics, our data suggests that the distribution of cascades size follows a power-law and heavy-tailed property with the slope approximately −2, and the common motifs of cascades with different topics are very similar, above 93% of them are isolated nodes. In order to find the formative motivity of hot cascades, we find that they always evolve to the structures like ‘star pattern’ and ‘two-polar pattern’, which are mainly due to the indegree of participating nodes, and are also correlated with the content of tweet.