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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 (97th percentile)

Mentioned by

news
2 news outlets
blogs
3 blogs
policy
1 policy source
twitter
29 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
189 Dimensions

Readers on

mendeley
284 Mendeley
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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

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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 29 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 284 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 1%
Switzerland 3 1%
Italy 3 1%
United Kingdom 3 1%
Portugal 2 <1%
China 2 <1%
Brazil 1 <1%
Belgium 1 <1%
Finland 1 <1%
Other 2 <1%
Unknown 262 92%

Demographic breakdown

Readers by professional status Count As %
Student > Master 55 19%
Student > Ph. D. Student 49 17%
Researcher 39 14%
Student > Bachelor 24 8%
Student > Doctoral Student 18 6%
Other 51 18%
Unknown 48 17%
Readers by discipline Count As %
Economics, Econometrics and Finance 63 22%
Computer Science 49 17%
Business, Management and Accounting 36 13%
Physics and Astronomy 19 7%
Engineering 13 5%
Other 49 17%
Unknown 55 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 74. 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 01 June 2020.
All research outputs
#578,933
of 25,402,528 outputs
Outputs from PLOS ONE
#7,888
of 221,290 outputs
Outputs of similar age
#2,771
of 178,120 outputs
Outputs of similar age from PLOS ONE
#102
of 4,039 outputs
Altmetric has tracked 25,402,528 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 221,290 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one has done particularly well, scoring higher than 96% 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 178,120 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 4,039 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 97% of its contemporaries.