Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Correction

Correction: Computational Fact Checking from Knowledge Networks

  • Giovanni Luca Ciampaglia,
  • Prashant Shiralkar,
  • Luis M. Rocha,
  • Johan Bollen,
  • Filippo Menczer,
  • Alessandro Flammini
  • Article
  • Metrics
  • Comments
  • Media Coverage

There is an error in the last sentence of the “Validation on factual statements” section of the Results. The sentence should read: With this method we estimate that, in the four subject areas, true statements are assigned higher truth values than false ones with probability 95%, 98%, 100%, and 95%, respectively.

Fig 4 is incorrect. Please view the corrected figure below.

thumbnail
Download:
Fig 4. Receiver Operating Characteristic for the multiple questions task.

https://doi.org/10.1371/journal.pone.0141938.g001

For each confusion matrix depicted in Fig 3 we compute ROC curves where true statements correspond to the diagonal and false statements to off-diagonal elements. The red dashed line represents the performance of a random classifier.

Reference

  1. 1. Ciampaglia GL, Shiralkar P, Rocha LM, Bollen J, Menczer F, Flammini A (2015) Computational Fact Checking from Knowledge Networks. PLoS ONE 10(6): e0128193. pmid:26083336

Citation: Ciampaglia GL, Shiralkar P, Rocha LM, Bollen J, Menczer F, Flammini A (2015) Correction: Computational Fact Checking from Knowledge Networks. PLoS ONE 10(10): e0141938. https://doi.org/10.1371/journal.pone.0141938

Published: October 27, 2015

Copyright: © 2015 Ciampaglia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited