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Encyclopedia of Big Data Technologies pp 1718–1726Cite as

Truth Discovery

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Introduction

In the era of Big Data, volume, velocity, and variety are commonly used to characterize the salient features of Big Data. However, the importance of veracity, the fourth “V” of Big Data, is now well-recognized as a critical dimension that needs to be assessed by joint solutions coming from various research communities such as natural language processing (NLP), database (DB), and machine learning (ML), as well as from data science practitioners and journalists (Cohen et al. 2011; Berti-Équille 2016). The problem of estimating veracity of online information in presence of multiple conflicting data is very challenging: information extraction suffers from uncertainties and errors; information sources may be dependent or colluded; and misinformation is evolving and spreading fast in complex social networks. All these aspects have to be well-understood to be properly modeled in order to detect and combat effectively fake news and misinformation campaigns.

Rumor detection,...

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Author information

Authors and Affiliations

  1. Aix-Marseille University, CNRS, LIS, Marseille, France

    Laure Berti-Équille

Authors
  1. Laure Berti-Équille
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Correspondence to Laure Berti-Équille .

Editor information

Editors and Affiliations

  1. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Sherif Sakr

  2. School of Information Technologies, Sydney University, Sydney, Australia

    Albert Y. Zomaya

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Berti-Équille, L. (2019). Truth Discovery. In: Sakr, S., Zomaya, A.Y. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-77525-8_23

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