New techniques to measure lie detection using COVID-19 fake news and the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2)

Fake news, disinformation and misinformation in social media: a review

Online social networks (OSNs) are rapidly growing and have become a huge source of all kinds of global and local news for millions of users. However, OSNs are a double-edged sword. Although the great advantages they offer such as unlimited easy communication and instant news and information, they can also have many disadvantages and issues. One of their major challenging issues is the spread of fake news. Fake news identification is still a complex unresolved issue. Furthermore, fake news detection on OSNs presents unique characteristics and challenges that make finding a solution anything but trivial. On the other hand, artificial intelligence (AI) approaches are still incapable of overcoming this challenging problem. To make matters worse, AI techniques such as machine learning and deep learning are leveraged to deceive people by creating and disseminating fake content. Consequently, automatic fake news detection remains a huge challenge, primarily because the content is designed in a way to closely resemble the truth, and it is often hard to determine its veracity by AI alone without additional information from third parties. This work aims to provide a comprehensive and systematic review of fake news research as well as a fundamental review of existing approaches used to detect and prevent fake news from spreading via OSNs. We present the research problem and the existing challenges, discuss the state of the art in existing approaches for fake news detection, and point out the future research directions in tackling the challenges.

Who falls for fake news? Psychological and clinical profiling evidence of fake news consumers

Awareness of the potential psychological significance of false news increased during the coronavirus pandemic, however, its impact on psychopathology and individual differences remains unclear. Acknowledging this, the authors investigated the psychological and psychopathological profiles that characterize fake news consumption. A total of 1452 volunteers from the general population with no previous psychiatric history participated. They responded to clinical psychopathology assessment tests. Respondents solved a fake news screening test, which allowed them to be allocated to a quasi-experimental condition: group 1 (non-fake news consumers) or group 2 (fake news consumers). Mean comparison, Bayesian inference, and multiple regression analyses were applied. Participants with a schizotypal, paranoid, and histrionic personality were ineffective at detecting fake news. They were also more vulnerable to suffer its negative effects. Specifically, they displayed higher levels of anxiety and committed more cognitive biases based on suggestibility and the Barnum Effect. No significant effects on psychotic symptomatology or affective mood states were observed. Corresponding to these outcomes, two clinical and therapeutic recommendations related to the reduction of the Barnum Effect and the reinterpretation of digital media sensationalism were made. The impact of fake news and possible ways of prevention are discussed.

Classifying the Mexican epidemiological semaphore colour from the Covid-19 text Spanish news

This work aims to generate classification models that help determine the colour of an epidemiological semaphore (ES) by analysing online news and being better prepared for the different changes in the evolution of the pandemic. To accomplish this, we introduce Cov-NES-Mex corpus, a collection of 77,983 news (labelled with the Mexican ES system) related to Covid-19 for the 32 regions of Mexico. Also, we showed measures that describe the corpus as imbalanced and with a high vocabulary overlap between classes. In addition, evaluation measurements of the pandemic by region are proposed. Furthermore, a classification model, based on a transformer architecture specialised for the Spanish language, achieved up to 0.83 of F-measure. Thus, this work provides evidence that there is essential information in the news that can be used to determine the colour of the ES up to 4 weeks in advance. Finally, the presented results could be applied to other Spanish-speaking countries, which do not have an ES system, thus inferring and comparing their situation concerning the Mexican ES.

Impact of conspiracist ideation and psychotic-like experiences in patients with schizophrenia during the COVID-19 crisis

Conspiratorial belief is a type of argument that accepts implausible explanations in situations of great uncertainty or mystery. Claiming that the coronavirus is an artificial fabrication of laboratories is an example of conspiracist belief. The aim of this research was to analyze the impact of conspiracist ideation and psychotic-like experiences in patients with schizophrenia, patients with other mental disorders, and participants with no psychiatric history with a 132-day follow-up during the COVID-19 crisis. Analysis of variance (ANOVA) was applied and Bayesian inferences were carried out. The results conclude that conspiracist ideation and psychotic-like experiences increased significantly after 132 days of social-health restrictions in the general population. However, psychotic-like experiences did not increase in patients with schizophrenia. Conspiracist ideation has a quantitative degradation similar to the continuum model of psychosis; it is present both in patients with schizophrenia and in those participants with no clinical history. The psychopathological value of conspiracist ideation within the spectrum of psychosis is discussed.

Statistical indicators of compliance with anti-COVID-19 public health measures at European airports

International travel and the infrastructures involved are key elements in controlling and predicting the number of infections by an infectious disease (specifically COVID-19 cases). This research presents the rates or percentages of compliance with COVID-19 mitigation measures at several international airports in Europe (Madrid, Dublin, Paris-Charles de Gaulle, Zurich, Barcelona, and Bilbao). A structured survey called the COVID-19 Measures Implementation Rate at Airports (MIRA) was developed. First, the validity and reliability of the measurements obtained by MIRA were analyzed. A total of 1239 volunteers (passengers, cabin crew, and ground crew) participated in the study and answered the MIRA questionnaire. Second, once the validity and reliability of the measurements were assured, the rates or percentages of cases that observed compliance with the mitigation measures were calculated. The results indicated that participants perceived a low degree of compliance with sanitary measures in their international travel (the proportions ranged from 52.6% to 59%). The airports with the highest compliance with mitigation measures were the Dublin (with a rate of 70%) and Zurich airports (with a rate of 69.1%). In conclusion, the percentages could be low due to the ineffective implementation of some of the mitigation measures. The low percentages are not related to the health measures themselves. The implications of mitigation measures for containing the transmission of infectious diseases such as COVID-19 are discussed.

Critical thinking predicts reductions in Spanish physicians' stress levels and promotes fake news detection

The prevalence of pseudoscientific beliefs and fake news increased during the coronavirus crisis. Misinformation streams such as these potentially pose risks to people's health. Thus, knowing how these pseudoscientific beliefs and fake news impact the community of internists may be useful for improving primary care services. In this research, analyses of stress levels, effectiveness in detecting fake news, use of critical thinking (CP), and attitudes toward pseudosciences in internists during the COVID-19 crisis were performed. A total of 1129 internists participated. Several multiple regression models were applied using the forward stepwise method to determine the weight of CP and physicians' attitudes toward pseudosciences in predicting reductions in stress levels and facilitating the detection of fake news. The use of critical thinking predicted 46.9% of the reduction in stress levels. Similarly, skeptical attitudes and critical thinking predicted 56.1% of the hits on fake news detection tests. The stress levels of physicians during the coronavirus pandemic were clinically significant. The efficacy of fake news detection increases by 30.7% if the individual was a physician. Study outcomes indicate that the use of critical thinking and skeptical attitudes reduce stress levels and allow better detection of fake news. The importance of how to promote critical and skeptical attitudes in the field of medicine is discussed.

The Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2): A Psychometric Alternative to Measure and Explain Supernatural Experiences

This paper presents the English adaptation of the Multivariable Multiaxial Suggestibility Inventory-2 (MMSI-2), a questionnaire developed specifically for psychological assessment and prediction of anomalous phenomena. The sample consisted of 613 respondents from England (47.6% were women and 52.4% men). All of them were of legal age (mean = 34.5; standard deviation = 8.15). An exploratory factor analysis was applied, and three confirmatory factor models were adjusted. Omega coefficients and test-retest designs were used for reliability analysis. The MMSI-2 has a valid internal structure consisting of five macrofactors: Clinical Personality Tendencies (CPT), Anomalous Perceived Phenomena (APP), Incoherent Manipulations (IMA), Altered States of Consciousness (ASC), and Openness (OP). Omega coefficients for CPT and OP factors were low but acceptable. Furthermore, test-retest trials were excellent for all scales and factors. The psychological factors CPT, IMA, and ASC predicted 18.3% of the variance of anomalous experiences (APP). The authors concluded the English MMSI-2 was a valid and reliable test for the evaluation of anomalous phenomena but recommend that subsequent research reviews the predictive quality of the underlying model.