Dataset Information

Deception Detection in Politics: Can Voters Tell When Politicians are Lying?

ABSTRACT: In this study, we investigate voters' unaided perceptions of whether politicians are lying. We conduct an experiment in which participants attempt to uncover politicians' dishonesty by watching videos of their speeches. We find that verbal cues (specifically, the amount of detail in the speech) and general demeanor cues explain the success (failure) of veracity judgments far better than paraverbal and nonverbal cues. We also find evidence of a truth bias-people are more likely to judge statements to be true than false-despite the political setting, where voters might have been more skeptical. However, gender plays a deterministic role for veracity judgments in political context; female politicians are more likely to be judged as honest.

SUBMITTER: Mattes K

PROVIDER: S-EPMC8378529 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Deception Detection in Politics: Can Voters Tell When Politicians are Lying?

Mattes Kyle K Popova Valeriia V Evans Jacqueline R JR

Political behavior 20210820 1

In this study, we investigate voters' unaided perceptions of whether politicians are lying. We conduct an experiment in which participants attempt to uncover politicians' dishonesty by watching videos of their speeches. We find that verbal cues (specifically, the amount of detail in the speech) and general demeanor cues explain the success (failure) of veracity judgments far better than paraverbal and nonverbal cues. We also find evidence of a truth bias-people are more likely to judge statement ...[more]

PMID: 34456405

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Project description:Deception is an impactful social event that has been the focus of an abundance of researches over recent decades. In this paper, an electroencephalography (EEG) study is presented regarding the cognitive processes of an instructed liar/truth-teller during the time window of stimulus (question) delivery period (SDP) prior to their deceptive/truthful responses towards questions related to authentic (WE: with prior experience) and fictional experience (NE: no prior experience). To investigate deception in non-experienced events, the subjects were given stimuli in a mock interview scenario that induced them to fabricate lies. To analyze the data, frequency domain network and connectivity analysis was performed in the source space in order to provide a more systematic level understanding of deception during SDP. This study reveals several groups of neuronal generators underlying both the instructed lying (IL) and the instructed truth-telling (IT) conditions for both tasks during the SDP. Despite the similarities existed in these group components, significant differences were found in the intra- and inter-group connectivity between the IL and IT conditions in either task. Additionally, the response time was found to be positively correlated with the clustering coefficient of the inferior frontal gyrus (44R) in the WE-IL condition and positively correlated with the clustering coefficient of the precuneus (7L) and the angular gyrus (39R) in the WE-IT condition. However, the response time was found to be marginally negatively correlated with the clustering coefficient of the secondary auditory cortex (42L) in the NE-IL condition and negatively correlated with the clustering coefficient of the somatosensory association cortex (5L, R) in the NE-IT condition. Therefore, these results provide complementary and intuitive evidence for the differences between the IL and IT conditions in SDP for two types of deception tasks, thus elucidating the electrophysiological mechanisms underlying SDP of deception from regional, inter-regional, network, and inter-network scale analyses.

Project description:AimResearch on deception detection has usually been executed in experimental settings in the laboratory. In contrast, the present research investigates deception detection by actual victims and near victims of fraud, as reported in their own words.Materials and methodsOur study is based on a nationally representative survey of 11 types of (mostly) online fraud victimization (N = 2,864). We used qualitative information from actual victims and near victims on why they didn't fall for the fraud, or how, in hindsight, it could have been prevented.ResultsThe main detection strategies mentioned by near victims (N = 958) were 1) fraud knowledge (69%): these near victims clearly recognized fraud. Other strategies related to fraud knowledge were: noticing mistakes (27.9%), rules and principles about safe conduct (11.7%), and personal knowledge (7.1%). A second type of strategy was distrust (26.1%). A third strategy was 'wise through experience' (1.6%). Finally, a limited number of respondents (7.8%) searched for additional information: they contacted other people (5.5%), sought information online (4%), contacted the fraudster (2.9%), contacted their bank or credit card company (2.2%), or contacted the police (0.2%). Using knowledge as a strategy decreases the probability of victimization by a factor of 0.43. In contrast, all other strategies increased the likelihood of victimization by a factor of 1.6 or more. Strategies generally were uncorrelated, several strategies differed by type of fraud. About 40% of the actual victims (N = 243) believed that their victimization might have been prevented by: 1) seeking information (25.2%), 2) paying more attention (18.9%), 3) a third party doing something (16.2%), 4) following safety rules or principles, like using a safer way of paying or trading (14.4%), or by 5) 'simply not going along with it' (10.8%). Most of these strategies were associated with a higher, not lower, likelihood of victimization.ConclusionClearly, knowledge of fraud is the best strategy to avoid fraud victimization. Therefore, a more proactive approach is needed to inform the public about fraud and attackers' modus operandi, so that potential victims already have knowledge of fraud upon encountering it. Just providing information online will not suffice to protect online users.

Dataset Information

Deception Detection in Politics: Can Voters Tell When Politicians are Lying?

Publications

Deception Detection in Politics: Can Voters Tell When Politicians are Lying?

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