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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Linguistic concreteness of statements of true and false intentions
AU - Calderon, Sofia
AU - Mac Giolla, Erik
AU - Luke, Timothy J.
AU - Warmelink, Lara
AU - Ask, Karl
AU - Granhag, Pär Anders
AU - Vrij, Aldert
PY - 2023/12/1
Y1 - 2023/12/1
N2 - Our aim was to examine how people communicate their true and false intentions. Based on construal-level theory (Trope & Liberman, 2010), we predicted that statements of true intentions would be more concretely phrased than statements of false intentions. True intentions refer to more likely future events than false intentions, and they should therefore be mentally represented at a lower level of mental construal. This should be mirrored in more concrete language use. Transcripts of truthful and deceptive statements about intentions from six previous experimental studies (total N = 528) were analyzed using two automated verbal content analysis approaches: a folk-conceptual measure of concreteness (Brysbaert et al., 2014) and linguistic category model scoring (Seih et al., 2017). Contrary to our hypotheses, veracity did not predict statements’ concreteness scores, suggesting that automated verbal analysis of linguistic concreteness is not a viable deception detection technique for intentions.
AB - Our aim was to examine how people communicate their true and false intentions. Based on construal-level theory (Trope & Liberman, 2010), we predicted that statements of true intentions would be more concretely phrased than statements of false intentions. True intentions refer to more likely future events than false intentions, and they should therefore be mentally represented at a lower level of mental construal. This should be mirrored in more concrete language use. Transcripts of truthful and deceptive statements about intentions from six previous experimental studies (total N = 528) were analyzed using two automated verbal content analysis approaches: a folk-conceptual measure of concreteness (Brysbaert et al., 2014) and linguistic category model scoring (Seih et al., 2017). Contrary to our hypotheses, veracity did not predict statements’ concreteness scores, suggesting that automated verbal analysis of linguistic concreteness is not a viable deception detection technique for intentions.
KW - Applied Psychology
KW - Clinical Psychology
KW - Experimental and Cognitive Psychology
UR - https://psyarxiv.com/h7g8b/
U2 - 10.1037/mac0000077
DO - 10.1037/mac0000077
M3 - Journal article
VL - 12
SP - 531
EP - 541
JO - Journal of Applied Research in Memory and Cognition
JF - Journal of Applied Research in Memory and Cognition
SN - 2211-3681
IS - 4
ER -