Photographs can distort memory for the news

Garry, Maryanne; Strange, Deryn; Bernstein, Daniel M.; Kinzett, Toni

doi:10.1002/acp.1362

Cited by 38 publications

(32 citation statements)

References 16 publications

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“…Indeed, media speculation about the possibility of protests preceded both the Olympic torch relay and the Royal Wedding-although both events in reality occurred with minimal disruption (Gibson & Walker, 2012;Malik, 2011)-and subjects might have even imagined these hypothetical protests at the time of the media coverage. We know that photos can lead people to elaborate on the information they receive, and to then believe they actually saw or heard those elaborated details (e.g., Garry, Strange, Bernstein, & Kinzett, 2007;Henkel, 2012). Therefore, the images of unrest in the convincing and unconvincing doctored photos could have encouraged subjects to retrieve relevant mental imagery, which they might in turn have misattributed to their recollections of the target events via a feature importation mechanism (Henkel & Carbuto, 2008;Johnson, Hashtroudi, & Lindsay, 1993;Lyle & Johnson, 2006).…”

Section: Discussionmentioning

confidence: 99%

Changing beliefs about past public events with believable and unbelievable doctored photographs

Nash

2017

Memory

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Doctored photographs can shape what people believe and remember about prominent public events, perhaps due to their apparent credibility. In three studies, subjects completed surveys about the 2012 London Olympic torch relay (Experiment 1) or the 2011 Royal Wedding of Prince William and Kate Middleton (Experiments 2-3). Some were shown a genuine photo of the event; others saw a doctored photo that depicted protesters and unrest. A third group of subjects saw a doctored photo whose inauthenticity had been made explicit, either by adding a written disclaimer (Experiment 1) or by making the digital manipulation deliberately poor (Experiments 2-3). In all three studies, doctored photos had small effects on a subset of subjects' beliefs about the events. Of central interest though, comparable effects also emerged when the photos were overtly inauthentic. These findings suggest that cognitive mechanisms other than credibility - such as familiarity misattribution and mental imagery - can rapidly influence beliefs about past events even when the low credibility of a source is overt.

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Section: Discussionmentioning

confidence: 99%

Changing beliefs about past public events with believable and unbelievable doctored photographs

Nash

2017

Memory

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“…In a study by Henkel (2011) the participants performed a series of actions (phase 1), later on viewed a series of photos representing finished actions (phase 2), then performed a memory test (phase 3).…”

Section: Introductionmentioning

confidence: 99%

The role of kinematic mental simulation in creating false memories

Ianì

Mazzoni

Bucciarelli

2018

Journal of Cognitive Psychology

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Our investigation focuses on memory for scenes depicted in photos. According to the mental model theory, the observation of a static scene depicted in a photo which portrays an actor near to perform an action can trigger a kinematic mental simulation of that action unfolding in time. The deriving prediction is that such kinematic mental model supports the creation of a false memory of the actor performing an advanced phase of the action. We test this prediction in three experiments in which participants are presented with static scenes of actions, and after three days they perform a recognition task in which they assess recognition of old and novel static scenes depicting actions. The results confirm that false memories occur for actions that represent the unfolding over time of the static action initially observed. Our theoretical framework can accommodate also several previous findings in the literature on false memories.

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“…In a different study, this time not including fake images but highlighting the power of images to influence humans, Garry et al [22] proposed an experiment to measure how images affect people's memory for the news. As described by the authors, participants have been presented to a hurricane news which describes its effects on a village located at a coastal region.…”

Section: The Image Powermentioning

confidence: 99%

Visual Computing and Machine Learning Techniques for Digital Forensics

Carvalho

Pedrini

Rocha

2015

RITA

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A rapidez com que diversos campos da ciência vêm avançando dia após dia é notável. Em especial, os avanços tecnológicos têm impressionado muitas pessoas, uma vez que introduzem em suas vidas fatos que vão além da imaginação. Inspirados em métodos anteriormente apresentados por programas de ficção científica, a comunidade ligada à área de Computação criou um novo campo de pesquisa denominado Análise Forense de Documentos Digitais, o qual foca em desenvolver e implantar métodos capazes de auxiliar na luta contra crimes digitais, tais como a falsificação de imagens digitais. Este artigo apresenta alguns dos principais conceitos relacionados à Análise Forense de Documentos Digitais e, de forma complementar, apresenta algumas das mais recentes e poderosas técnicas baseadas em conceitos provenientes das áreas de Computação Gráfica, Processamento de Imagens, Visão Computacional e Aprendizado de Máquina para detectar falsificações em fotografias digitais. Alguns tópicos que são abordados neste trabalho incluem: atribuição de fonte, detecção de ataques, detecção de pornografia, filogenia multimídia e detecção de falsificações. Por fim, este trabalho destaca os desafios e problemas em aberto no campo da Análise Forense de Imagens Digitais para que os leitores se familiarizem com as oportunidades de pesquisa disponíveis. Visual Computing and Machine Learning Techniques for Digital ForensicsAbstract: It is impressive how fast science has improved day by day in so many different fields. In special, technology advances are shocking so many people bringing to their reality facts that previously were beyond their imagination. Inspired by methods earlier presented in scientific fiction shows, the computer science community has created a new research area named Digital Forensics, which aims at developing and deploying methods for fighting against digital crimes such as digital image forgery. This work presents some of the main concepts associated with Digital Forensics and, complementarily, presents some recent and powerful techniques relying on Computer Graphics, Image Processing, Computer Vision and Machine Learning concepts for detecting forgeries in photographs. Some topics addressed in this work include: source attribution, spoofing detection, pornography detection, multimedia phylogeny, and forgery detection. Finally, this work highlights the challenges and open problems in Digital Image Forensics to provide the readers with the myriad opportunities available for research.

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Photographs can distort memory for the news

Cited by 38 publications

References 16 publications

Changing beliefs about past public events with believable and unbelievable doctored photographs

Changing beliefs about past public events with believable and unbelievable doctored photographs

The role of kinematic mental simulation in creating false memories

Visual Computing and Machine Learning Techniques for Digital Forensics

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