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Web Search Queries Can Predict Stock Market Volumes

Overview of attention for article published in PLoS ONE, July 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
2 news outlets
blogs
2 blogs
twitter
14 tweeters
wikipedia
1 Wikipedia page

Citations

dimensions_citation
91 Dimensions

Readers on

mendeley
160 Mendeley
Title
Web Search Queries Can Predict Stock Market Volumes
Published in
PLoS ONE, July 2012
DOI 10.1371/journal.pone.0040014
Pubmed ID
Authors

Ilaria Bordino, Stefano Battiston, Guido Caldarelli, Matthieu Cristelli, Antti Ukkonen, Ingmar Weber, Bordino I, Battiston S, Caldarelli G, Cristelli M, Ukkonen A, Weber I

Abstract

We live in a computerized and networked society where many of our actions leave a digital trace and affect other people's actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www.

Twitter Demographics

The data shown below were collected from the profiles of 14 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 4%
Italy 3 2%
United Kingdom 3 2%
China 2 1%
Portugal 2 1%
Switzerland 2 1%
Australia 1 <1%
Brazil 1 <1%
Finland 1 <1%
Other 4 3%
Unknown 135 84%

Demographic breakdown

Readers by professional status Count As %
Student > Master 37 23%
Student > Ph. D. Student 35 22%
Researcher 33 21%
Student > Bachelor 14 9%
Student > Doctoral Student 8 5%
Other 33 21%
Readers by discipline Count As %
Economics, Econometrics and Finance 36 23%
Computer Science 35 22%
Business, Management and Accounting 19 12%
Physics and Astronomy 16 10%
Engineering 9 6%
Other 45 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 50. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 April 2016.
All research outputs
#243,529
of 11,302,850 outputs
Outputs from PLoS ONE
#5,290
of 125,914 outputs
Outputs of similar age
#1,906
of 107,632 outputs
Outputs of similar age from PLoS ONE
#99
of 3,262 outputs
Altmetric has tracked 11,302,850 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 125,914 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 107,632 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 3,262 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.