基于时空和事件的twitter话题流行度分析

Proceedings of the 22nd ACM international conference on Information & Knowledge Management Pub Date : 2013-10-27 DOI:10.1145/2505515.2505525

S. Ardon, A. Bagchi, A. Mahanti, Amit Ruhela, Aaditeshwar Seth, R. M. Tripathy, Sipat Triukose

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引用次数: 63

摘要

我们首次对Twitter上的思想传播进行了全面表征，研究了超过596万个话题，其中包括热门话题和不太热门的话题。在包含大约1000万用户和1.96亿条推文的数据集上，我们执行了严格的时间和空间分析，调查了由讨论每个主题的用户形成的子图的时间演变属性。我们关注两种不同的空间概念:由Twitter上的关注者-关注者链接形成的网络拓扑，以及用户的地理空间位置。我们研究了发起者对话题受欢迎程度的影响，发现拥有大量关注者的用户对话题受欢迎程度有很强的影响。我们推断，当讨论话题的不相关的用户群开始合并并形成一个巨大的组成部分，并逐渐覆盖网络的很大一部分时，话题就会变得流行起来。我们的地理空间分析表明，最受欢迎的话题是那些积极跨越区域边界的话题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Spatio-temporal and events based analysis of topic popularity in twitter

We present the first comprehensive characterization of the diffusion of ideas on Twitter, studying more than 5.96 million topics that include both popular and less popular topics. On a data set containing approximately 10 million users and a comprehensive scraping of 196 million tweets, we perform a rigorous temporal and spatial analysis, investigating the time-evolving properties of the subgraphs formed by the users discussing each topic. We focus on two different notions of the spatial: the network topology formed by follower-following links on Twitter, and the geospatial location of the users. We investigate the effect of initiators on the popularity of topics and find that users with a high number of followers have a strong impact on topic popularity. We deduce that topics become popular when disjoint clusters of users discussing them begin to merge and form one giant component that grows to cover a significant fraction of the network. Our geospatial analysis shows that highly popular topics are those that cross regional boundaries aggressively.

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Proceedings of the 22nd ACM international conference on Information & Knowledge Management

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