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Cited by 267

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Why the Pirate Party Won the German Election of 2009 or The Trouble With Predictions: A Response to Tumasjan, A., Sprenger, T. O., Sander, P. G., & Welpe, I. M. “Predicting Elections With Twitter: What 140 Characters Reveal About Political Sentiment”

Jungherr, Andreas, Jürgens, Pascal, Schoen, Harald·2012·Social Science Computer Review

Abstract

In their article “Predicting Elections with Twitter: What 140 Characters Reveal About Political Sentiment,” the authors Andranik Tumasjan, Timm O. Sprenger, Philipp G. Sandner, and Isabell M. Welpe (TSSW) the authors claim that it would be possible to predict election outcomes in Germany by examining the relative frequency of the mentions of political parties in Twitter messages posted during the election campaign. In this response we show that the results of TSSW are contingent on arbitrary choices of the authors. We demonstrate that as of yet the relative frequency of mentions of German political parties in Twitter message allows no prediction of election results.

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Metadata

Authors
Jungherr, A., Jürgens, P., & Schoen, H.
Venue
Social Science Computer Review
Published
2011-04-25
Volume
30
Issue
2
Pages
229-234
ISSN
  • 0894-4393 (ISSN-L)
  • 1552-8286
OpenAlex
W2116646433
Cited by
267
References
1
FWCI
57.31
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Why the Pirate Party Won the German Election of 2009 or The Trouble With Predictions: A Response to Tumasjan, A., Sprenger, T. O., Sander, P. G., & Welpe, I. M. “Predicting Elections With Twitter: What 140 Characters Reveal About Political Sentiment”. https://app.cochat.ai/papers/10.1177/0894439311404119
The paper
Jungherr, A., Jürgens, P., & Schoen, H. (2012). Why the Pirate Party Won the German Election of 2009 or The Trouble With Predictions: A Response to Tumasjan, A., Sprenger, T. O., Sander, P. G., & Welpe, I. M. “Predicting Elections With Twitter: What 140 Characters Reveal About Political Sentiment”. Social Science Computer Review. https://doi.org/10.1177/0894439311404119

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