Unlabelled: Disinformation (fake news) is a major problem that affects modern populations, especially in an era when information can be spread from one corner of the world to another in just one click. The diffusion of misinformation becomes more problematic when it addresses issues related to health, as it can affect people at both the individual and population levels. Through the ideas proposed by cultural evolution theory, in this study, we seek to understand the dynamics of disseminating messages (cultural traits) with untrue content (maladaptive traits). For our investigation, we used the scenario caused by the Coronavirus Disease 2019 (COVID-19) pandemic as a model. The instability caused by the pandemic provides a good model for the study of adapted and maladaptive traits, as the information can directly affect individual and population fitness. Through data collected on the Twitter platform (259,176 tweets) and using machine learning techniques and web scraping, we built a predictive model to analyze the following questions: (1) Is false information more shared? (2) Is false information more adopted? (3) Do people with social prestige influence the dissemination of maladaptive traits of COVID-19? We observed that fake news features contained in messages with false information were shared and adopted as unblemished messages. We also observed that social prestige was not a determining factor for the diffusion of maladaptive traits. Even with the ability to allow connections between individuals participating in social media, some factors such as attachment to cultural traits and the formation of social bubbles can favor isolation and decrease connectivity between individuals. Consequently, in the scenario of isolation between groups and low connectivity between individuals, there is a reduction in cultural exchange between people, which interferes with the dynamics of the selection of cultural traits. Thus, maladaptive (harmful) traits are favored and maintained in the cultural system. We also argue that the local Brazilian cultural context can be a determining factor for maintaining maladaptive traits. We conclude that in an unstable (pandemic) scenario, the information transmitted on Twitter is not reliable in relation to the increase in fitness, which may occur because of the low cultural exchange promoted by the personalization of the social network and cultural context of the population.
Supplementary Information: The online version contains supplementary material available at 10.1007/s42979-021-00836-w.
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http://dx.doi.org/10.1007/s42979-021-00836-w | DOI Listing |
J Pers Assess
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PersonaCura, Clinical Center of Excellence for Older Adults with Personality Disorders and Developmental Disorders, GGz Breburg, Tilburg, the Netherlands.
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School of Pharmacy and Biomedical Sciences, The University of Central Lancashire, Preston UK. Electronic address:
Personality disorders (PDs) are psychiatric conditions characterized by enduring patterns of cognition, emotion, and behaviour that deviate significantly from cultural norms, causing distress or impairment. The aetiology of PDs is complex, involving both genetic and environmental factors. Genetic studies estimate the heritability of PDs at 30% to 60%, implicating genes involved in neurotransmitter regulation, such as those for serotonin transporters and dopamine receptors.
View Article and Find Full Text PDFBrain Sci
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Department of Health Sciences, University "Magna Graecia" of Catanzaro, 88100 Catanzaro, Italy.
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View Article and Find Full Text PDFAnnu Rev Clin Psychol
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Department of Psychology, University of Kentucky, Lexington, Kentucky, USA; email:
The personality disorders are said to be at the vanguard in the shift to a dimensional model of classification, as exemplified in the Alternative Model of Personality (AMPD) presented in Section III of the fifth edition of the (DSM-5) for emerging models and in the 11th edition of the (ICD-11). Considered herein are some limitations and challenges. For the DSM-5 AMPD trait model, these include problematic placements, inadequate coverage, perceived complexity, and lack of cutoff points.
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