Complex dynamics of our economic life on different scales: insights from search engine query data
Complex dynamics of our economic life on different scales: insights from search engine query data
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DOI：
10.1098/rsta.2010.0284
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发表时间：
2010-12-28
期刊：
影响因子：
5
通讯作者：
Stanley, H. Eugene
中科院分区：
文献类型：
--
作者：
Preis, Tobias;Reith, Daniel;Stanley, H. Eugene
搜索引擎查询数据可以洞察我们经济生活中可能规模最小的个人的行为。人们每天在世界各地提交数亿次搜索引擎查询。我们研究 2004 年至 2010 年搜索引擎 Google 提供的各种搜索词的每周搜索量数据，用于科学用途，提供有关我们经济生活的总体集体信息。我们提出这样的问题：搜索量数据与每周时间范围内的金融市场波动之间是否存在联系。互联网用户的集体“群体智能”和金融市场参与者群体都可以被视为一个由许多相互作用的子单元组成的复杂系统，它们对外部变化做出快速反应。我们发现明确的证据表明，标准普尔 500 指数公司的每周交易量与相应公司名称的每周搜索量相关。此外，我们应用最近引入的方法来量化时间序列中的复杂相关性，我们发现搜索量时间序列和交易量时间序列显示出重复模式的明显趋势。
Search engine query data deliver insight into the behaviour of individuals who are the smallest possible scale of our economic life. Individuals are submitting several hundred million search engine queries around the world each day. We study weekly search volume data for various search terms from 2004 to 2010 that are offered by the search engine Google for scientific use, providing information about our economic life on an aggregated collective level. We ask the question whether there is a link between search volume data and financial market fluctuations on a weekly time scale. Both collective 'swarm intelligence' of Internet users and the group of financial market participants can be regarded as a complex system of many interacting subunits that react quickly to external changes. We find clear evidence that weekly transaction volumes of S&P 500 companies are correlated with weekly search volume of corresponding company names. Furthermore, we apply a recently introduced method for quantifying complex correlations in time series with which we find a clear tendency that search volume time series and transaction volume time series show recurring patterns.