Five shades of untruth: Finer-grained classification of fake news

Liqiang Wang, Yafang Wang, Gerard De Melo, Gerhard Weikum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Prior work on algorithmic truth assessment on unreliable content, has mostly pursued binary classifiers - factual vs. fake - and disregarded the finer shades of untruth. On the other hand, manual analysis of questionable content has proposed a more fine-grained classification: Distinguishing between hoaxes, irony and propaganda, or the six-way rating by the PolitiFact community. In this paper, we present a principled approach to capture these finer shades in automatically assessing and classifying news articles and claims. We systematically explore a variety of signals from both news and social media, and give an analysis of the underlying features.

Original languageEnglish (US)
Title of host publicationProceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
EditorsAndrea Tagarelli, Chandan Reddy, Ulrik Brandes
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages593-594
Number of pages2
ISBN (Electronic)9781538660515
DOIs
StatePublished - Oct 24 2018
Event10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018 - Barcelona, Spain
Duration: Aug 28 2018Aug 31 2018

Publication series

NameProceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018

Other

Other10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
CountrySpain
CityBarcelona
Period8/28/188/31/18

All Science Journal Classification (ASJC) codes

  • Sociology and Political Science
  • Communication
  • Computer Networks and Communications
  • Information Systems and Management

Keywords

  • fake news
  • finegrained classification
  • social media
  • unreliable content

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