新浪微博拓扑与信息传播的测量与分析

Pengyi Fan, Pei Li, Zhihong Jiang, Wei Li, Hui Wang
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引用次数: 18

摘要

新浪微博是中国最早、规模最大的微博服务,已成为最受欢迎的信息传播媒介之一。为了深入了解中国微博网络的拓扑和信息扩散特征,我们对新浪微博进行了大约3个月的抓取,获得了其拓扑和话题的轨迹。与其他在线社交网络相比,我们的测量研究显示了一些有趣的发现。我们的数据表明,新浪微博网络具有明显的小世界效应和无标度特征,特别是外度分布呈现出多个不同指数的独立幂律区。我们还观察到,新浪微博的叠加图呈现出分类混合模式,且关联度和关联度呈弱相关。此外,通过构建不同主题的级联,我们的数据表明,级联大小的分布遵循幂律和重尾性质,斜率近似为- 2,并且不同主题的级联的共同基元非常相似,其中93%以上是孤立节点。为了寻找热级联的形成动力,我们发现它们总是演变成“星型”和“两极型”的结构,这主要是由于参与节点的程度,也与tweet的内容相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Measurement and analysis of topology and information propagation on Sina-Microblog
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.
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