标题： 使用转发图动态建模Twitter中的趋势 显示英文标题

标题： Modelling of trends in Twitter using retweet graph dynamics

摘要： 在本文中，我们对Twitter中的用户行为进行建模，以捕捉热门话题的出现。 为此，我们首先对多个不同事件的推文数据集进行了广泛分析。 特别是，对于这些数据集，我们构建并研究了转发图。 我们发现，热门话题的转发图具有相对密集的最大连通分量（LCC）。 接下来，基于从数据集分析中获得的见解，我们设计了一个数学模型，该模型通过三个主要参数描述转发图的演变。 然后，我们通过分析和模拟量化了模型参数对转发图基本特性（如边的密度以及LCC的大小和密度）的影响。 最后，我们将模型投入实际应用，估计其参数，并将模型的结果行为与我们的数据集进行比较。 显示英文摘要

摘要： In this paper we model user behaviour in Twitter to capture the emergence of trending topics. For this purpose, we first extensively analyse tweet datasets of several different events. In particular, for these datasets, we construct and investigate the retweet graphs. We find that the retweet graph for a trending topic has a relatively dense largest connected component (LCC). Next, based on the insights obtained from the analyses of the datasets, we design a mathematical model that describes the evolution of a retweet graph by three main parameters. We then quantify, analytically and by simulation, the influence of the model parameters on the basic characteristics of the retweet graph, such as the density of edges and the size and density of the LCC. Finally, we put the model in practice, estimate its parameters and compare the resulting behavior of the model to our datasets.