Recent Developments in Statement Analysis

Steller, Max

doi:10.1007/978-94-015-7856-1_8

Cited by 125 publications

(156 citation statements)

References 4 publications

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“…When predictive linguistic cues are developed based on general linguistic knowledge (Höfer et al, 1996), linguistic cues could be portable to social media contexts (for instance, from e-mail to full-sentences forum posts). Nevertheless, if the subject areas are highly specialized, then when deciphering predictive cues, researchers should account for context specificity and format (Höfer et al, 1996, Porter and Yuille, 1996a, Köhnken and Steller, 1988, Steller, 1989. Table 1 summarizes various types of discourses or types of data that were addressed within various disciplines that study deceptive behaviors and their linguistic predictors.…”

Section: Methodological Solutions: Deception Detection With Linguistimentioning

confidence: 99%

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Deception Detection and Rumor Debunking for Social Media

Rubin¹

2016

The SAGE Handbook of Social Media Research Methods

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The main premise of this chapter is that the time is ripe for more extensive research and development of social media tools that filter out intentionally deceptive information such as deceptive memes, rumors and hoaxes, fake news or other fake posts, tweets and fraudulent profiles. Social media users' awareness of intentional manipulation of online content appears to be relatively low, while the reliance on unverified information (often obtained from strangers) is at an all-time high. I argue there is need for content verification, systematic fact-checking and filtering of social media streams. This literature survey provides a background for understanding current automated deception detection research, rumor debunking, and broader content verification methodologies, suggests a path towards hybrid technologies, and explains why the development and adoption of such tools might still be a significant challenge. Biographical DetailsVictoria L. Rubin is an Associate Professor at the Faculty of Information and Media Studies and the Director of the Language and Information Technologies Research Lab (LiT.RL) at the University of Western Ontario. She specializes in information retrieval and natural language processing techniques that enable analyses of texts to identify, extract, and organize structured knowledge. She studies complex human information behaviors that are, at least partly, expressed through language such as deception, uncertainty, credibility, and emotions. Her research on Deception Detection has been published in recent core workshops on the topic and prominent information science conferences, as well as the

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Section: Methodological Solutions: Deception Detection With Linguistimentioning

confidence: 99%

“…This trend necessitates the need for significant enhancements in the analytical tools that help analysts detect influence bots (Subrahmanian et al, 2016).…”

Section: Astroturfing By Social Botsmentioning

confidence: 99%

Deception Detection and Rumor Debunking for Social Media

Rubin¹

2016

The SAGE Handbook of Social Media Research Methods

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“…Se manipularon dos condiciones experimentales. Primera, en la condición de memoria de hechos vividos (auto-experimentados, memoria autobiográfica) se pedió a los participantes que narraran la memoria de un hecho vivido (como ejemplos se les proporcionaron los referidos en el DSM-5 como eventos traumáticos, tal como un la muerte o enfermedad de un familiar, operación quirúrgica o un accidente de tráfico) que cumpliera los criterios descritos por Steller (1989) para que fuera equiparable a la memoria obtenida en las evaluaciones forenses: implicación personal, tono emocional negativo del evento, y una gran pérdida de control. Segunda, en la condición de memoria fabricada de hechos se les presentó un material en vídeo de un robo solicitándoles que tomaran el testimonio como propio (experimentación directa) narrándolo como vivido (auto-experimentado).…”

Section: Método •Participantesunclassified

“…Además, los contenidos de lo visionado estaban fuera dl control de los actores. De este modo se cumplían las condiciones (experimentación del evento como propio, carácter negativo del evento y situación fuera del control del observador) de una simulación de alta fidelidad (Steller, 1989).…”

Section: Método •Participantesunclassified

¿Son los criterios de realidad válidos para clasificar y discernir entre memorias de hechos auto-experimentados y de eventos vistos en vídeo?

Monteiro¹,

Vázquez²,

Seijo³

et al. 2017

Rev. iberoam. psicol. salud

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“…This research is driven by numerous theories which explain why liars may differ from truth-tellers in the verbal contents of speech and/or the nonverbal behaviours they exhibit while describing those events. For example, the theory of Reality Monitoring (RM) suggests that those who have engaged in a real event report different details within the contents of their speech than those who report an imagined event (that never occurred) because the source of each "memory" is comprised of different qualities (e.g., Steller, 1989;Vrij, Akehurst, Soukara, & Bull, 2004). In this theory, accounts of real events are assumed to be analogous to truthful accounts, whereas reports of imagined events are thought to parallel deceptive reports.…”

Section: Purported Versus Valid Cues Used To Detect Deceptionmentioning

confidence: 99%

Truth and Deception in Informants' Accounts of Criminal Admissions

Boydell¹

2012

PsycEXTRA Dataset

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Informants who report admissions to crime can be powerful and dangerous players in the criminal justice system. Some informants, such as jailhouse informants, are considered deceitful, in part because they can receive incentives to report criminal admissions. However, little research has examined the nature of information that informants provide. In particular, no recent published research has examined whether there are valid behavioural cues that distinguish deceptive from truthful informants. In addition, no published study to date has explored whether informants' reports and demeanours are affected by the incentives that they receive. Participants in this study either did or did not hear a criminal admission and then were interviewed one week later about details of the admission they had allegedly heard. Some participants were offered an incentive to report the criminal admission in a way that appeared accurate and forthcoming. The results of this study suggest that there may be behavioural cues emitted during the reporting of criminal admissions that distinguish truthful from deceptive informants. However, the direction of differences for some cues may deviate from other types of witnesses to crime. In addition, the findings of this study indicate that being offered an incentive may induce informants to emit cues during the reporting of criminal admissions that make them appear more truthful, regardless of whether or not they are actually telling the truth. The findings of this study raise concerns about whether informants' honesty should be assessed in the same way as other witnesses, and about potentially negative consequences of offering incentives to informants in exchange for their reports of criminal admissions.

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Recent Developments in Statement Analysis

Cited by 125 publications

References 4 publications

Deception Detection and Rumor Debunking for Social Media

Deception Detection and Rumor Debunking for Social Media

¿Son los criterios de realidad válidos para clasificar y discernir entre memorias de hechos auto-experimentados y de eventos vistos en vídeo?

Truth and Deception in Informants' Accounts of Criminal Admissions

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