de Oliveira Danilo Vicente Batista, Albuquerque Ulysses Paulino
Laboratório de Ecologia e Evolução de Sistemas Socioecológicos (LEA), Departamento de Botânica, Universidade Federal de Pernambuco, Av. Prof. Moraes Rego, 1235, Cidade Universitária, Recife, Pernambuco 50670-901 Brazil.
SN Comput Sci. 2021;2(6):430. doi: 10.1007/s42979-021-00836-w. Epub 2021 Aug 28.
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.
The online version contains supplementary material available at 10.1007/s42979-021-00836-w.
虚假信息（假新闻）是影响现代人群的一个主要问题，尤其是在一个信息只需一键就能从世界的一个角落传播到另一个角落的时代。当虚假信息涉及健康相关问题时，其传播会带来更多问题，因为它会在个体和群体层面影响人们。通过文化进化理论提出的观点，在本研究中，我们试图理解传播带有不实内容（不良适应性特征）的信息（文化特征）的动态过程。对于我们的调查，我们将2019年冠状病毒病（COVID - 19）大流行引发的情况用作模型。大流行造成的不稳定为研究适应性和不良适应性特征提供了一个良好模型，因为信息可直接影响个体和群体的适应性。通过在推特平台上收集的数据（259,176条推文）并使用机器学习技术和网络爬虫，我们构建了一个预测模型来分析以下问题：（1）虚假信息是否更易被分享？（2）虚假信息是否更易被采纳？（3）具有社会声望的人是否会影响COVID - 19不良适应性特征的传播？我们观察到，包含虚假信息的消息中的假新闻特征被当作无瑕疵的消息进行分享和采纳。我们还观察到，社会声望并非不良适应性特征传播的决定性因素。即使社交媒体能够让参与其中的个体建立联系，但诸如对文化特征的依恋以及社会泡沫的形成等一些因素会助长隔离并减少个体之间的联系。因此，在群体隔离和个体之间联系薄弱的情况下，人们之间的文化交流减少，这会干扰文化特征的选择动态。于是，不良适应性（有害）特征在文化系统中受到青睐并得以维持。我们还认为，巴西当地的文化背景可能是维持不良适应性特征的一个决定性因素。我们得出结论，在不稳定（大流行）的情况下，推特上传播的信息在与适应性增加相关方面不可靠，这可能是由于社交网络的个性化以及人群的文化背景所促进的文化交流较少所致。
在线版本包含可在10.1007/s42979 - 021 - 00836 - w获取的补充材料。
