Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Quantifying the semantics of search behavior before stock market moves

Tools
- Tools
+ Tools

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 ISSN 0027-8424.

Research output not available from this repository.

Request-a-Copy directly from author or use local Library Get it For Me service.

Official URL: http://dx.doi.org/10.1073/pnas.1324054111

Request Changes to record.

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
Divisions: Faculty of Social Sciences > Warwick Business School > Behavioural Science
Faculty of Social Sciences > Warwick Business School
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:
DateEvent
12 August 2014Published
28 July 2014Available
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

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item
twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us