scholarly journals Does explaining the origins of misinformation improve the effectiveness of a given correction?

2022 ◽  
Author(s):  
Saoirse Connor Desai ◽  
Stian Reimers

Misinformation often has a continuing influence on event-related reasoning even when it is clearly and credibly corrected; this is referred to as the continued influence effect. The present work investigated whether a correction’s effectiveness can be improved by explaining how the misinformation originated. Two experiments examined whether a correction that explained misinformation as originating from intentional deception, or an unintentional error were more effective than a correction that only identified the misinformation as false. Experiment 1 found that corrections which explained the misinformation as intentionally or unintentionally misleading were as effective as a correction that was not accompanied by an explanation for how the misinformation originated. We replicated this in Experiment 2 and found substantial attenuation of thecontinued influence effect in a novel scenario with the same underlying structure.Overall, the results suggest that informing people that the misinformation originated from a deliberate lie or accidental error may not be an effective correction strategy over and above stating that the misinformation is false.

2020 ◽  
Author(s):  
Hua Jin ◽  
Lina Jia ◽  
Xiaojuan Yin ◽  
Shilin Wei ◽  
Guiping Xu

Misinformation often continues to influence people’s cognition even after corrected (the ‘continued influence effect of misinformation’, the CIEM). This study investigated the role of information relevance in the CIEM by questionnaire survey and experimental study. The results showed that information with higher relevance to the individuals had a larger CIEM, indicating a role of information relevance in the CIEM. Personal involvement might explain the effects of information relevance on the CIEM. This study provides insightful clues for reducing the CIEM in different types of misinformation and misinformation with varying relevance.


2018 ◽  
Vol 18 (3) ◽  
pp. 467-477 ◽  
Author(s):  
Solveig Engebretsen ◽  
Arnoldo Frigessi ◽  
Kenth Engø-Monsen ◽  
Anne-Sofie Furberg ◽  
Audun Stubhaug ◽  
...  

Abstract Background and aims Twin studies have found that approximately half of the variance in pain tolerance can be explained by genetic factors, while shared family environment has a negligible effect. Hence, a large proportion of the variance in pain tolerance is explained by the (non-shared) unique environment. The social environment beyond the family is a potential candidate for explaining some of the variance in pain tolerance. Numerous individual traits have previously shown to be associated with friendship ties. In this study, we investigate whether pain tolerance is associated with friendship ties. Methods We study the friendship effect on pain tolerance by considering data from the Tromsø Study: Fit Futures I, which contains pain tolerance measurements and social network information for adolescents attending first year of upper secondary school in the Tromsø area in Northern Norway. Pain tolerance was measured with the cold-pressor test (primary outcome), contact heat and pressure algometry. We analyse the data by using statistical methods from social network analysis. Specifically, we compute pairwise correlations in pain tolerance among friends. We also fit network autocorrelation models to the data, where the pain tolerance of an individual is explained by (among other factors) the average pain tolerance of the individual’s friends. Results We find a significant and positive relationship between the pain tolerance of an individual and the pain tolerance of their friends. The estimated effect is that for every 1 s increase in friends’ average cold-pressor tolerance time, the expected cold-pressor pain tolerance of the individual increases by 0.21 s (p-value: 0.0049, sample size n=997). This estimated effect is controlled for sex. The friendship effect remains significant when controlling for potential confounders such as lifestyle factors and test sequence among the students. Further investigating the role of sex on this friendship effect, we only find a significant peer effect of male friends on males, while there is no significant effect of friends’ average pain tolerance on females in stratified analyses. Similar, but somewhat lower estimates were obtained for the other pain modalities. Conclusions We find a positive and significant peer effect in pain tolerance. Hence, there is a significant tendency for students to be friends with others with similar pain tolerance. Sex-stratified analyses show that the only significant effect is the effect of male friends on males. Implications Two different processes can explain the friendship effect in pain tolerance, selection and social transmission. Individuals might select friends directly due to similarity in pain tolerance, or indirectly through similarity in other confounding variables that affect pain tolerance. Alternatively, there is an influence effect among friends either directly in pain tolerance, or indirectly through other variables that affect pain tolerance. If there is indeed a social influence effect in pain tolerance, then the social environment can account for some of the unique environmental variance in pain tolerance. If so, it is possible to therapeutically affect pain tolerance through alteration of the social environment.


NeuroImage ◽  
1997 ◽  
Vol 5 (4) ◽  
pp. 280-291 ◽  
Author(s):  
Sherri Gold ◽  
Stephan Arndt ◽  
Debra Johnson ◽  
Daniel S. O'Leary ◽  
Nancy C. Andreasen

Game Theory ◽  
2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Nicholas S. Kovach ◽  
Alan S. Gibson ◽  
Gary B. Lamont

When dealing with conflicts, game theory and decision theory can be used to model the interactions of the decision-makers. To date, game theory and decision theory have received considerable modeling focus, while hypergame theory has not. A metagame, known as a hypergame, occurs when one player does not know or fully understand all the strategies of a game. Hypergame theory extends the advantages of game theory by allowing a player to outmaneuver an opponent and obtaining a more preferred outcome with a higher utility. The ability to outmaneuver an opponent occurs in the hypergame because the different views (perception or deception) of opponents are captured in the model, through the incorporation of information unknown to other players (misperception or intentional deception). The hypergame model more accurately provides solutions for complex theoretic modeling of conflicts than those modeled by game theory and excels where perception or information differences exist between players. This paper explores the current research in hypergame theory and presents a broad overview of the historical literature on hypergame theory.


2020 ◽  
Author(s):  
Ullrich K. H. Ecker ◽  
Stephan Lewandowsky ◽  
Matthew Chadwick

Misinformation often continues to influence inferential reasoning after clear and credible corrections are provided; this effect is known as the continued influence effect. It has been theorized that this effect is partly driven by misinformation familiarity. Some researchers have even argued that a correction should avoid repeating the misinformation, as the correction itself could serve to inadvertently enhance misinformation familiarity and may thus backfire, ironically strengthening the very misconception it aims to correct. While previous research has found little evidence of such familiarity backfire effects, there remains one situation where they may yet arise: when correcting entirely novel misinformation, where corrections could serve to spread misinformation to new audiences who had never heard of it before. This article presents three experiments (total N = 1,718) investigating the possibility of familiarity backfire within the context of correcting novel misinformation claims and after a one-week study-test delay. While there was variation across experiments, overall there was substantial evidence against familiarity backfire. Corrections that exposed participants to novel misinformation did not lead to stronger misconceptions compared to a control group never exposed to the false claims or corrections. This suggests that it is safe to repeat misinformation when correcting it, even when the audience might be unfamiliar with the misinformation.


PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0255067
Author(s):  
Annamaria Ficara ◽  
Lucia Cavallaro ◽  
Francesco Curreri ◽  
Giacomo Fiumara ◽  
Pasquale De Meo ◽  
...  

Data collected in criminal investigations may suffer from issues like: (i) incompleteness, due to the covert nature of criminal organizations; (ii) incorrectness, caused by either unintentional data collection errors or intentional deception by criminals; (iii) inconsistency, when the same information is collected into law enforcement databases multiple times, or in different formats. In this paper we analyze nine real criminal networks of different nature (i.e., Mafia networks, criminal street gangs and terrorist organizations) in order to quantify the impact of incomplete data, and to determine which network type is most affected by it. The networks are firstly pruned using two specific methods: (i) random edge removal, simulating the scenario in which the Law Enforcement Agencies fail to intercept some calls, or to spot sporadic meetings among suspects; (ii) node removal, modeling the situation in which some suspects cannot be intercepted or investigated. Finally we compute spectral distances (i.e., Adjacency, Laplacian and normalized Laplacian Spectral Distances) and matrix distances (i.e., Root Euclidean Distance) between the complete and pruned networks, which we compare using statistical analysis. Our investigation identifies two main features: first, the overall understanding of the criminal networks remains high even with incomplete data on criminal interactions (i.e., when 10% of edges are removed); second, removing even a small fraction of suspects not investigated (i.e., 2% of nodes are removed) may lead to significant misinterpretation of the overall network.


Sign in / Sign up

Export Citation Format

Share Document