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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 10 of 10 1 MUMBAI: multi-person, multimodal board game affect and interaction analysis dataset [<Journal>] Doyran, Metehan [Verfasser]; Schimmel, Arjan [Verfasser]; Baki, Pınar [Verfasser]. DNB Subject Category Language Show details 2 A Personal Model of Trumpery: Linguistic Deception Detection in a Real-World High-Stakes Setting ... Van Der Zee, Sophie; Poppe, Ronald; Havrileck, Alice. - : SAGE Journals, 2021 BASE Show details 3 A Personal Model of Trumpery: Linguistic Deception Detection in a Real-World High-Stakes Setting ... Van Der Zee, Sophie; Poppe, Ronald; Havrileck, Alice. - : SAGE Journals, 2021 BASE Show details 4 Datasets and code of the paper: 'A personal model of trumpery: Linguistic deception detection in a real-world high-stakes setting' ... van der Zee, Sophie; Baillon, Aurelien; Poppe, Ronald; Havrileck, Alice. - : Erasmus University Rotterdam (EUR), 2021 Abstract: Paper abstract Language use differs between truthful and deceptive statements, but not all differences are consistent across people and contexts, complicating the identification of deceit in individuals. By relying on fact-checked tweets, we show in three studies (Study 1: 469 tweets; Study 2: 484 tweets; Study 3: 24 models) how well personalized linguistic deception detection performs by developing the first deception model tailored to an individual: the 45th US president. First, we found substantial linguistic differences between factually correct and incorrect tweets. We developed a quantitative model and achieved 73% overall accuracy. Second, we tested out-of-sample prediction and achieved 74% overall accuracy. Third, we compared our personalized model to linguistic models previously reported in the literature. Our model outperformed existing models by 5pp, demonstrating the added value of personalized linguistic analysis in real-world settings. Our results indicate that factually incorrect tweets by the ... Keyword: 170104 Forensic Psychology; Applied Psychology; FOS Other medical sciences; Personality, Social and Criminal Psychology URL: https://dx.doi.org/10.25397/eur.17179514.v1 https://datarepository.eur.nl/articles/dataset/Datasets_and_code_of_the_paper_A_personal_model_of_trumpery_Linguistic_deception_detection_in_a_real-world_high-stakes_setting_/17179514/1 BASE Hide details 5 sj-docx-1-pss-10.1177_09567976211015941 – Supplemental material for A Personal Model of Trumpery: Linguistic Deception Detection in a Real-World High-Stakes Setting ... Van Der Zee, Sophie; Poppe, Ronald; Havrileck, Alice. - : SAGE Journals, 2021 BASE Show details 6 Datasets and code of the paper: 'A personal model of trumpery: Linguistic deception detection in a real-world high-stakes setting' ... van der Zee, Sophie; Baillon, Aurelien; Poppe, Ronald. - : Erasmus University Rotterdam (EUR), 2021 BASE Show details 7 sj-docx-1-pss-10.1177_09567976211015941 – Supplemental material for A Personal Model of Trumpery: Linguistic Deception Detection in a Real-World High-Stakes Setting ... Van Der Zee, Sophie; Poppe, Ronald; Havrileck, Alice. - : SAGE Journals, 2021 BASE Show details 8 Multitask Learning to Improve Egocentric Action Recognition ... Kapidis, Georgios; Poppe, Ronald; van Dam, Elsbeth. - : arXiv, 2019 BASE Show details 9 A personal model of trumpery: Deception detection in a real-world high-stakes setting ... van der Zee, Sophie; Poppe, Ronald; Havrileck, Alice. - : arXiv, 2018 BASE Show details 10 Virtual meeting rooms: from observation to simulation Reidsma, Dennis; Akker, Rieks; Rienks, Rutger... In: AI & society. - Guildford : Springer-Verl. London 22 (2008) 2, 133-144 OLC Linguistik Show details

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