THE INFLUENCE OF COVID-19 INFORMATION ON WHATSAPP SOCIAL MEDIA TOWARDS COMMUNITY ANXIETY LEVEL

Many people in the Sorogenen Village and Mitra Griya Asri Housing communities are concerned about the COVID-19 information spread via the WhatsApp group social media. The goal of this study was to see how exposure to COVID-19 information on WhatsApp affected anxiety levels in the hamlet and housing communities, as well as to look at how exposure to COVID-19 information on WhatsApp affected anxiety levels in the communities. The Uses and Gratification Theory, Information Exposure Theory, Anxiety Theory, and Individual Difference Theory are all investigated in this study. The quantitative research method was applied, with each sample area consisting of 100 participants. All of the ideas employed in this study were evaluated on the designated population, according to the findings. The findings of the hypothesis 1 test show that the greater the exposure to COVID-19 information on WhatsApp, the higher the residents of Sorogenen Padukuhan's anxiety level. Hypothesis 2 was tested, claiming that the higher the level of exposure to COVID-19 information on WhatsApp social media, the higher the level of anxiety among Mitra Griya Asri Housing residents; and hypothesis 3 was tested, claiming that there is a difference in the effect of COVID-19 information on the people of the communities, but no difference in the level of anxiety among these residents. This research provides scientific contributions in the form of indicators of critical thinking to strengthen active audiences on Uses and Gratification Theory and intensity indicators on Information Exposure Theory.

From Chatter to Action: How Social Networks Inform and Motivate in Rural Uganda

From public health to political campaigns, numerous attempts to encourage behavior begin with the spread of information. Of course, seeding new information does not guarantee action, especially when it is difficult for receivers to verify this information. We use a novel design that introduced valuable, actionable information in rural Uganda and reveals the intermediate process that led many in the village to hear the information but only some to act on it. We find that the seeded information spread easily through word of mouth via a simple contagion process. However, acting on the information spread less easily; this process relied instead on endogenously created social information that served to vet, verify, and pass judgment. Our results highlight an important wedge between information that a policy intervention can best control and the behavior that ultimately results.

Role-Aware Information Spread in Online Social Networks

Understanding the complex process of information spread in online social networks (OSNs) enables the efficient maximization/minimization of the spread of useful/harmful information. Users assume various roles based on their behaviors while engaging with information in these OSNs. Recent reviews on information spread in OSNs have focused on algorithms and challenges for modeling the local node-to-node cascading paths of viral information. However, they neglected to analyze non-viral information with low reach size that can also spread globally beyond OSN edges (links) via non-neighbors through, for example, pushed information via content recommendation algorithms. Previous reviews have also not fully considered user roles in the spread of information. To address these gaps, we: (i) provide a comprehensive survey of the latest studies on role-aware information spread in OSNs, also addressing the different temporal spreading patterns of viral and non-viral information; (ii) survey modeling approaches that consider structural, non-structural, and hybrid features, and provide a taxonomy of these approaches; (iii) review software platforms for the analysis and visualization of role-aware information spread in OSNs; and (iv) describe how information spread models enable useful applications in OSNs such as detecting influential users. We conclude by highlighting future research directions for studying information spread in OSNs, accounting for dynamic user roles.

Comparing information diffusion mechanisms by matching on cascade size

Do some types of information spread faster, broader, or further than others? To understand how information diffusions differ, scholars compare structural properties of the paths taken by content as it spreads through a network, studying so-called cascades. Commonly studied cascade properties include the reach, depth, breadth, and speed of propagation. Drawing conclusions from statistical differences in these properties can be challenging, as many properties are dependent. In this work, we demonstrate the essentiality of controlling for cascade sizes when studying structural differences between collections of cascades. We first revisit two datasets from notable recent studies of online diffusion that reported content-specific differences in cascade topology: an exhaustive corpus of Twitter cascades for verified true- or false-news content by Vosoughi et al. [S. Vosoughi, D. Roy, S. Aral. Science 359, 1146–1151 (2018)] and a comparison of Twitter cascades of videos, pictures, news, and petitions by Goel et al. [S. Goel, A. Anderson, J. Hofman, D. J. Watts. Manage. Sci. 62, 180–196 (2016)]. Using methods that control for joint cascade statistics, we find that for false- and true-news cascades, the reported structural differences can almost entirely be explained by false-news cascades being larger. For videos, images, news, and petitions, structural differences persist when controlling for size. Studying classical models of diffusion, we then give conditions under which differences in structural properties under different models do or do not reduce to differences in size. Our findings are consistent with the mechanisms underlying true- and false-news diffusion being quite similar, differing primarily in the basic infectiousness of their spreading process.

Fake news knowledge profile in Brazil during the COVID-19 pandemic

During the COVID-19 pandemic, a lot of false information spread through social networks, reaching different community groups, and contributing to the failure in the prevention and correct treatment of the disease. This study aimed to outline the profile of people who received fake news related to health during the SARS-CoV-2 pandemic in 2020. This is a descriptive study with a quantitative approach carried out by health academics through a self-administered questionnaire made on Google Forms. A sample of 501 participants was obtained to analyze the participant sociodemographic profile, the content, and the most used ways of receiving fake news. The results indicate that the most received content by the participants was about health, followed by politics. According to the study, traditional communication media are the most reliable source in the search for information among participants, while WhatsApp and Facebook were cited as the most used social media in the dissemination of fake news, with the least reliable news. There is a need for further studies on this topic, to demonstrate which sociodemographic factors, influence the sharing of fake news.

Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention

CommunityRx (CRx), an information technology intervention, provides patients with a personalized list of healthful community resources (HealtheRx). In repeated clinical studies, nearly half of those who received clinical “doses” of the HealtheRx shared their information with others (“social doses”). Clinical trial design cannot fully capture the impact of information diffusion, which can act as a force multiplier for the intervention. Furthermore, experimentation is needed to understand how intervention delivery can optimize social spread under varying circumstances. To study information diffusion from CRx under varying conditions, we built an agent-based model (ABM). This study describes the model building process and illustrates how an ABM provides insight about information diffusion through in silico experimentation. To build the ABM, we constructed a synthetic population (“agents”) using publicly-available data sources. Using clinical trial data, we developed empirically-informed processes simulating agent activities, resource knowledge evolution and information sharing. Using RepastHPC and chiSIM software, we replicated the intervention in silico, simulated information diffusion processes, and generated emergent information diffusion networks. The CRx ABM was calibrated using empirical data to replicate the CRx intervention in silico. We used the ABM to quantify information spread via social versus clinical dosing then conducted information diffusion experiments, comparing the social dosing effect of the intervention when delivered by physicians, nurses or clinical clerks. The synthetic population (N = 802,191) exhibited diverse behavioral characteristics, including activity and knowledge evolution patterns. In silico delivery of the intervention was replicated with high fidelity. Large-scale information diffusion networks emerged among agents exchanging resource information. Varying the propensity for information exchange resulted in networks with different topological characteristics. Community resource information spread via social dosing was nearly 4 fold that from clinical dosing alone and did not vary by delivery mode. This study, using CRx as an example, demonstrates the process of building and experimenting with an ABM to study information diffusion from, and the population-level impact of, a clinical information-based intervention. While the focus of the CRx ABM is to recreate the CRx intervention in silico, the general process of model building, and computational experimentation presented is generalizable to other large-scale ABMs of information diffusion.

Problematika Penggunaan Gadget dalam Pembelajaran Masa Pandemi Covid-19 (Dampak dan Solusi bagi Kesehatan Siswa)

The purpose of this study was to determine the effect of learning innovation during the Covid-19 pandemic and its relation to students' physical and mental health. The method used was a qualitative method using library research. The study showed that during the Covid-19 Pandemic, the teachers and students conducted their teaching and learning using media such as laptops, smartphones, or tablets connected through the network by providers or WiFi. Students' physical health was distracted due to the duration of using those media was too long. At the same time, insufficient supervision by parents also affected their psychological health since all information spread very quickly without any qualified filter. However, teachers also experienced the same cases as students' have. This study suggests that parents should take action not only to monitor the duration of their children's learning but also the content they access.

Information Warfare in Health Sector – Sifting ‘Real’ from ‘Fake’ News (Preprint)

UNSTRUCTURED Information warfare (IW) involves manipulation, destruction, or denying access to information altogether while maintaining the target’s trust. Psychological operations, a type of IW, concern the majority of the public as it aims to degrade their morale through infodemic and fake news. Fake news related to healthcare was present even before the COVID-19 pandemic. A broad range of content comes under it, like communication of inaccurate information with or without any intention to cause harm, mistaken interpretation of satires, and information spread with definitive socio-political agenda. We discuss the various facets of fake news including its burden in the health sector, pathogenesis, the different psychological perspectives of its spread, and strategies to counter it.

Developmental differences in perceptual anticipation underlie different sensitivities to coarticulatory dynamics

Anticipatory coarticulation is an indispensable feature of speech dynamics contributing to spoken language fluency. Research has shown that children speak with greater degrees of vowel anticipatory coarticulation than adults – that is, greater vocalic influence on previous segments. The present study examined how developmental differences in anticipatory coarticulation transfer to the perceptual domain. Using a gating paradigm, we tested 29 seven-year-olds and 93 German adult listeners with sequences produced by child and adult speakers, hence corresponding to low versus high vocalic anticipatory coarticulation degrees. First, children predicted vowel targets less successfully than adults. Second, greater perceptual accuracy was found for low compared to highly coarticulated speech. We propose that variations in coarticulation degrees reflect perceptually important differences in information dynamics and that listeners are more sensitive to fast changes in information than to a large amount of vocalic information spread across long segmental spans.