FIMS Graduate Research Day

On April 14, 2016 our lab presented a poster at the FIMS Research Day. The work is based on the project that aims to identify fake news. Satirical news, if mistaken for legitimate reporting, often pose a problem by misleading readers. A full paper associated with this poster is stored in ResearchGate repository. The paper will be presented at the specialized Workshop on Computational Approaches to Deception Detection (NAACL-CADD, San Diego) in June 2016. More details on both the poster and full paper are below.

Truth_or_MereTruthiness_poster_FIMS_ResearchDay_2016 Truth_or_Mere_Truthiness_Poster_Rubin_etal_2016_ProblemStatement Truth_or_Mere_Truthiness_Poster_Rubin_etal_2016_METHOD_RESULTS

 

FakeNews_or_Truth_Rubin_etal_2016_NAACL-HLT-CADD

Fake News or Truth? Using Satirical Cues to Detect Potentially Misleading News.

Abstract

Satire is an attractive subject in deception detection research: it is a type of deception that intentionally incorporates cues revealing its own deceptiveness. Whereas other types of fabrications aim to instill a false sense of truth in the reader, a successful satirical hoax must eventually be exposed as a jest. This paper provides a conceptual overview of satire and humor, elaborating and illustrating the unique features of satirical news, which mimics the format and style of journalistic reporting. Satirical news stories were carefully matched and examined in contrast with their legitimate news counterparts in 12 contemporary news topics in 4 domains (civics, science, business, and “soft” news). Building on previous work in satire detection, we proposed an SVM-based algorithm, enriched with 5 predictive features (Absurdity, Humor, Grammar, Negative Affect, and Punctuation) and tested their combinations on 360 news articles. Our best predicting feature combination (Absurdity, Grammar and Punctuation) detects satirical news with a 90% precision and 84% recall (F-score=87%). Our work in algorithmically identifying satirical news pieces can aid in minimizing the potential deceptive impact of satire. [Note: The associated dataset of the Satirical and Legitimate News, S-n-L News DB 2015-2016, is available via http://victoriarubin.fims.uwo.ca/news-verification/ . The set is password-protected to avoid automated harvesting. Please feel free to request the password, if you are interested.]

 

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