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探索网络中的默认模式和信息流。

Exploring default mode and information flow on the web.

机构信息

Center for Knowledge Structuring, The University of Tokyo, Hongo, Tokyo, Japan.

出版信息

PLoS One. 2013 Apr 24;8(4):e60398. doi: 10.1371/journal.pone.0060398. Print 2013.

Abstract

Social networking services (e.g., Twitter, Facebook) are now major sources of World Wide Web (called "Web") dynamics, together with Web search services (e.g., Google). These two types of Web services mutually influence each other but generate different dynamics. In this paper, we distinguish two modes of Web dynamics: the reactive mode and the default mode. It is assumed that Twitter messages (called "tweets") and Google search queries react to significant social movements and events, but they also demonstrate signs of becoming self-activated, thereby forming a baseline Web activity. We define the former as the reactive mode and the latter as the default mode of the Web. In this paper, we investigate these reactive and default modes of the Web's dynamics using transfer entropy (TE). The amount of information transferred between a time series of 1,000 frequent keywords in Twitter and the same keywords in Google queries is investigated across an 11-month time period. Study of the information flow on Google and Twitter revealed that information is generally transferred from Twitter to Google, indicating that Twitter time series have some preceding information about Google time series. We also studied the information flow among different Twitter keywords time series by taking keywords as nodes and flow directions as edges of a network. An analysis of this network revealed that frequent keywords tend to become an information source and infrequent keywords tend to become sink for other keywords. Based on these findings, we hypothesize that frequent keywords form the Web's default mode, which becomes an information source for infrequent keywords that generally form the Web's reactive mode. We also found that the Web consists of different time resolutions with respect to TE among Twitter keywords, which will be another focal point of this paper.

摘要

社交网络服务(例如,Twitter、Facebook)现在是万维网(称为“Web”)动态的主要来源,与 Web 搜索服务(例如,Google)一起。这两种类型的 Web 服务相互影响,但产生不同的动态。在本文中,我们区分了 Web 动态的两种模式:反应模式和默认模式。假设 Twitter 消息(称为“推文”)和 Google 搜索查询会对重大社会运动和事件做出反应,但它们也表现出自激活的迹象,从而形成了基本的 Web 活动。我们将前者定义为 Web 的反应模式,将后者定义为 Web 的默认模式。在本文中,我们使用转移熵(TE)研究 Web 动态的这两种反应和默认模式。在 11 个月的时间内,研究了 Twitter 中 1000 个频繁关键字的时间序列与 Google 查询中相同关键字之间的信息量转移。对 Google 和 Twitter 上信息流的研究表明,信息通常从 Twitter 转移到 Google,这表明 Twitter 时间序列对 Google 时间序列具有一定的先行信息。我们还通过将关键字作为节点,将流方向作为网络的边,研究了不同 Twitter 关键字时间序列之间的信息流。对该网络的分析表明,频繁的关键字往往成为信息源,而不频繁的关键字往往成为其他关键字的汇点。基于这些发现,我们假设频繁的关键字形成了 Web 的默认模式,它成为不频繁关键字的信息源,而不频繁的关键字通常形成了 Web 的反应模式。我们还发现,Web 具有不同的时间分辨率,这是本文的另一个重点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d19/3634805/0842885f5f94/pone.0060398.g001.jpg

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