Computational fact-checking: a content management perspective

Data journalism designates journalistic work inspired by digital data sources. A particularly popular and active area of data journalism is concerned with fact-checking. The term was born in the journalist community and referred the process of verifying and ensuring the accuracy of published media content; since 2012, however, it has increasingly focused on the analysis of politics, economy, science, and news content shared in any form, but first and foremost on the Web (social and otherwise). These trends have been noticed by computer scientists working in the industry and academia. Thus, a very lively area of digital content management research has taken up these problems and works to propose foundations (models), algorithms, and implement them through concrete tools. Our tutorial: (i) Outlines the current state of affairs in the area of digital (or computational) fact-checking in newsrooms, by journalists, NGO workers, scientists and IT companies; (ii) Shows which areas of digital content management research, in particular those relying on the Web, can be leveraged to help fact-checking, and gives a comprehensive survey of efforts in this area; (iii) Highlights ongoing trends, unsolved problems, and areas where we envision future scientific and practical advances.  S. Cazalens, J. Leblay, P. Lamarre, I. Manolescu, X. Tannier.  A Content Management Perspective. PVLDB, 11 (12): 2110-2113, 2018.  https://doi.org/10.14778/3229863.3229880  To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. For any use beyond those covered by this license, obtain permission by emailing info@vldb.org.   Section 1.2 discusses the scientific content management areas which bring useful tools for computational fact-checking. 1.1 Data journalism and fact-checking While data of some form is a natural ingredient of all reporting, the increasing volumes and complexity of digital data lead to a qualitative jump, where technical skills, and in particular data science skills, are stringently needed in journalistic work. A particularly popular and active area of data journalism is concerned with fact-checking. The term was born in the journalist community; it referred to the task of identifying and checking factual claims present in media content, which dedicated newsroom personnel would then check for factual accuracy. The goal of such checking was to avoid misinformation, to protect the journal reputation and avoid legal actions. Starting around 2012, first in the United States (FactCheck.org), then in Europe, and soon after in all areas of the world, journalists have started to take advantage of modern technologies for processing content, such as text, video, structured and unstructured data, in order to automate, at least partially, the knowledge finding, reasoning, and analysis tasks which had been previously performed completely by humans. Over time, the focus of fact-checking shifted from verifying claims made by media outlets, toward the claims made by politicians and other public figures. This trend coincided with the parallel (but distinct) evolution toward asking Government Open Data, that is: the idea that governing bodies should share with the public precise information describing their functioning, so that the people have means to assess the quality of their elected representation. Government Open Data became quickly available, in large volumes, e.g. through data.gov in the US, data.gov.uk in the UK, data.gouv.fr in France etc.; journalists turned out to be the missing link between the newly available data and comprehension by the public. Data journalism thus found http://factcheck.org