The art of the lie: Detecting deception in Donald Trump’s statements
Research output: Contribution to conference › Poster › peer-review
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2019. Poster session presented at Germanic Society for Forensic Linguistics , Graz, Austria.
Research output: Contribution to conference › Poster › peer-review
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TY - CONF
T1 - The art of the lie: Detecting deception in Donald Trump’s statements
AU - Shank, Christopher
AU - Foltz, Anoushka
PY - 2019/9
Y1 - 2019/9
N2 - The concepts of lying and deception have recently come to the forefront in American politics, with terms such as ‘pathological liar’, ‘post-truth’, and ‘fake news’ dominating political discourse. This project analyzes statements made by Donald Trump during the 2016 presidential debates, which were independently fact-checked and rated to be true, mostly true, half true, mostly false or false, to explore whether Trump’s speech and/or para-linguistic behavior could provide cues as to whether he was engaging in deception. We analyzed dysfluencies and hesitations, blink rate, gaze, gestures, and smiles. A double blind coding protocol was implemented - i.e. the coder did not know which statements were true or false when coding the statements. The results suggest that only blink rate and smiles showed promise in identifying whether or not Trump was lying. Specifically, Trump’s blink rate range increased when he made false or mostly false statements compared to true, mostly true and half true statements. Furthermore, Trump more frequently smiled with no involvement of the muscles around the eyes (which would indicate actual enjoyment) when lying than when telling the truth. Overall, neither Trump’s speech nor his body language provided cues for deception. Instead, some subtle changes in his facial dynamics provided cues to deception. Currently ongoing analyses are underway to explore whether response latency and speech rate may be additional cues to deception in Trump’s speech.
AB - The concepts of lying and deception have recently come to the forefront in American politics, with terms such as ‘pathological liar’, ‘post-truth’, and ‘fake news’ dominating political discourse. This project analyzes statements made by Donald Trump during the 2016 presidential debates, which were independently fact-checked and rated to be true, mostly true, half true, mostly false or false, to explore whether Trump’s speech and/or para-linguistic behavior could provide cues as to whether he was engaging in deception. We analyzed dysfluencies and hesitations, blink rate, gaze, gestures, and smiles. A double blind coding protocol was implemented - i.e. the coder did not know which statements were true or false when coding the statements. The results suggest that only blink rate and smiles showed promise in identifying whether or not Trump was lying. Specifically, Trump’s blink rate range increased when he made false or mostly false statements compared to true, mostly true and half true statements. Furthermore, Trump more frequently smiled with no involvement of the muscles around the eyes (which would indicate actual enjoyment) when lying than when telling the truth. Overall, neither Trump’s speech nor his body language provided cues for deception. Instead, some subtle changes in his facial dynamics provided cues to deception. Currently ongoing analyses are underway to explore whether response latency and speech rate may be additional cues to deception in Trump’s speech.
KW - Deception
KW - Trump
KW - blink rate
KW - gesture
M3 - Poster
T2 - Germanic Society for Forensic Linguistics
Y2 - 5 September 2019 through 8 September 2019
ER -