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Quantifying the semantics of search behavior before stock market moves
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Curme, Chester, Preis, Tobias, Stanley, H. Eugene and Moat, Helen Susannah (2014) Quantifying the semantics of search behavior before stock market moves. Proceedings of the National Academy of Sciences of the United States of America, Volume 111 (Number 32). pp. 11600-11605. doi:10.1073/pnas.1324054111
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Official URL: http://dx.doi.org/10.1073/pnas.1324054111
Abstract
Technology is becoming deeply interwoven into the fabric of society. The Internet has become a central source of information for many people when making day-to-day decisions. Here, we present a method to mine the vast data Internet users create when searching for information online, to identify topics of interest before stock market moves. In an analysis of historic data from 2004 until 2012, we draw on records from the search engine Google and online encyclopedia Wikipedia as well as judgments from the service Amazon Mechanical Turk. We find evidence of links between Internet searches relating to politics or business and subsequent stock market moves. In particular, we find that an increase in search volume for these topics tends to precede stock market falls. We suggest that extensions of these analyses could offer insight into large-scale information flow before a range of real-world events.
| Item Type: | Journal Article | ||||||
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| Divisions: | Faculty of Social Sciences > Warwick Business School > Behavioural Science Faculty of Social Sciences > Warwick Business School |
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| Journal or Publication Title: | Proceedings of the National Academy of Sciences of the United States of America | ||||||
| Publisher: | National Academy of Sciences | ||||||
| ISSN: | 0027-8424 | ||||||
| Official Date: | 12 August 2014 | ||||||
| Dates: |
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| Volume: | Volume 111 | ||||||
| Number: | Number 32 | ||||||
| Page Range: | pp. 11600-11605 | ||||||
| DOI: | 10.1073/pnas.1324054111 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Funder: | Research Councils UK (RCUK) | ||||||
| Grant number: | EP/K039830/1 |
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