论文标题
Twitter上信息级联的分支过程描述
Branching process descriptions of information cascades on Twitter
论文作者
论文摘要
对基于Twitter的信息级联反应进行了详细分析，并证明分支过程假设已近似满足。使用分支过程框架，比较了代理到代理传输的模型，得出的结论是，有限的注意模型比更常见的独立级联模型更好地再现数据的相关特征。现有的和新的分支过程分析结果表明与经验信息级联的重要统计特征非常匹配，从而证明了分支过程描述的力量，以理解社会信息传播。
A detailed analysis of Twitter-based information cascades is performed, and it is demonstrated that branching process hypotheses are approximately satisfied. Using a branching process framework, models of agent-to-agent transmission are compared to conclude that a limited attention model better reproduces the relevant characteristics of the data than the more common independent cascade model. Existing and new analytical results for branching processes are shown to match well to the important statistical characteristics of the empirical information cascades, thus demonstrating the power of branching process descriptions for understanding social information spreading.
