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Cited by 220

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

The power of prediction with social media

Open access
Schoen, Harald, Gayo-Avello, Daniel, Takis Metaxas, Panagiotis, Mustafaraj, Eni, Strohmaier, Markus, Gloor, Peter·2013·Internet Research
DOI 10.1108/intr-06-2013-0115
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Abstract

Notice: Changes introduced as a result of publishing processes such as copy-editing and formatting may not be reflected in this document. For a definitive version of this work, please refer to the published source.

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Cites

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Citations

Cites

Show all 7 references

Research works printed but not linked: 32

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  7. Forsythe, R. , Nelson, F.D. , Neumann, G.R. and Wright, J. (1992), “Anatomy of an experimental political stock market”, American Economic Review, Vol. 82 No. 5, pp. 1142-1163.
  8. 10.1080/19331681.2012.705080 · DOI
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  10. Gil, R. and Levitt, S.D. (2007), “Testing the efficiency of markets in the 2002 World Cup”, The Journal of Prediction Markets, Vol. 1 No. 3, pp. 255-270.
  11. Ginsberg, J. , Mohebbi, M.H. , Patel, R.S. , Brammer, L. , Smolinski, M.S. and Brilliant, L. (2009), “Detecting influenza epidemics using search engine query data”, Nature, Vol. 457 No. 19, pp. 1012-1014. · DOI · Paper page
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  19. 10.1017/S1049096500057607 · doi:10.1017/s1049096500057607 · Paper page
  20. Lampos, V. and Cristianini, N. (2012), “Nowcasting events from the social web with statistical learning”, ACM Transactions on Intelligent Systems and Technology (TIST), Vol. 3 No. 4, Article no. 72. · DOI · Paper page
  21. 10.1093/pan/mps002 · DOI · Paper page
  22. O'Connor, B. , Balasubramanyan, R. , Routledge, B.R. and Smith, N.A. (2010), “From tweets to polls: linking text sentiment to public opinion time series”, ICWSM, Vol. 11 pp. 122-129. · DOI · Paper page
  23. O'Connor, P. and Feng, Z. (2008), “The tradesports NFL prediction market: an analysis of market efficiency, transaction costs, and bettor preferences”, The Journal of Prediction Markets, Vol. 2 No. 1, pp. 45-71. · DOI
  24. 10.1561/1500000011 · DOI · Paper page
  25. 10.1126/science.291.5506.987 · DOI · Paper page
  26. 10.1086/268524 · DOI
  27. Polgreen, P.M. , Nelson, F.D. and Neumann, G.R. (2007), “Use of prediction markets to forecast infectious disease activity”, Healthcare Epidemiology, Vol. 47 No. 11, pp. 272-279. · DOI
  28. 10.1086/593098 · DOI · Paper page
  29. 10.1257/0895330041371277 · DOI · Paper page
  30. Signorini, A. , Segre, A.M. and Polgreen, P.M. (2011), “The use of Twitter to track levels of disease activity and public concern in the US during the influenza A H1N1 pandemic”, PLoS ONE, Vol. 6 No. 5, p. · DOI · Paper page
  31. 10.2469/faj.v57.n3.2449 · DOI · Paper page
  32. 10.1016/j.sbspro.2011.10.562 · DOI · Paper page

Cited by

See all 220

Metadata

Authors
Schoen, H., Gayo-Avello, D., Takis Metaxas, P., Mustafaraj, E., Strohmaier, M., & Gloor, P.
Venue
Internet Research
Publisher
Emerald
Published
2013-10-14
Volume
23
Issue
5
Pages
528-543
ISSN
1066-2243 (ISSN-L)
DOI
10.1108/intr-06-2013-0115
OpenAlex
W2137036358
Cited by
220
References
7
FWCI
29.92
Type
journal article
Language
en
Open access
green
Licence
www.emeraldinsight.com/page/tdm (tdm)

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CoChat. (2026). Citation check: The power of prediction with social media. https://app.cochat.ai/papers/10.1108/intr-06-2013-0115
The paper
Schoen, H., Gayo-Avello, D., Takis Metaxas, P., Mustafaraj, E., Strohmaier, M., & Gloor, P. (2013). The power of prediction with social media. Internet Research. https://doi.org/10.1108/intr-06-2013-0115

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.