Visual Analysis of Social Robots in Twitter on China Agenda Setting

With the development and progress of intelligent algorithms, more and more social robots are used to interfere with the information transmission and direction of international public opinion. This paper takes the agenda of COVID-19 in Twitter as the breakthrough point, and through the methods of web crawler, Twitter robot detection, data processing and analysis, aims at the agenda setting of social robots for China issues, that is, to carry out data visualization analysis for the stigmatized China image. Through case analysis, concrete and operable countermeasures for building the international communication system of China image were provided. © 2022 IEEE.

The Burden of Being a Bridge: Analysing Subjective Well-Being of Twitter Users During the COVID-19 Pandemic

The outbreak of the COVID-19 pandemic triggers infodemic over online social media, which significantly impacts public health around the world, both physically and psychologically. In this paper, we study the impact of the pandemic on the mental health of influential social media users, whose sharing behaviours significantly promote the diffusion of COVID-19 related information. Specifically, we focus on subjective well-being (SWB), and analyse whether SWB changes have a relationship with their bridging performance in information diffusion, which measures the speed and wideness gain of information transmission due to their sharing. We accurately capture users' bridging performance by proposing a new measurement. Benefiting from deep-learning natural language processing models, we quantify social media users' SWB from their textual posts. With the data collected from Twitter for almost two years, we reveal the greater mental suffering of influential users during the COVID-19 pandemic. Through comprehensive hierarchical multiple regression analysis, we are the first to discover the strong relationship between social users' SWB and their bridging performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Information transmission in regional energy stock markets.

Since markets are undergoing severe turbulent economic periods, this study investigates the information transmission of energy stock markets of five regions including North America, South America, Europe, Asia, and Pacific where we differentiated the regional energy markets based on their developing and developed state of economy. We employed time-frequency domain from Jan 1995 to May 2021 and found that energy stocks of developed regions are highly connected. The energy markets of North America, South America, and Europe are the net transmitters of spillovers, whereas the Asian and Pacific energy markets are the net receivers of spillovers. The results also reveal that the connectedness of regional energy markets is time and frequency dependent. Regional energy stocks were highly connected following the Asian financial crisis (AFC), global financial crisis (GFC), European debt crisis (EDC), shale oil revolution (SOR), and COVID-19 pandemic. Time-dependent results reveal that high spillovers formed during stress periods and frequency domain show the higher connectedness of regional energy stock markets in the short run followed by an extreme economic condition. These results have significant implications for policymakers, regulators, investors, and regional controlling bodies to adopt effective strategies during short run to avoid economic downturns and information distortions.

"Covid-19 is dangerous": The role of parental verbal threat information on children's fear of Covid-19.

INTRODUCTION: Theoretical and empirical evidence suggests that the effect of parental verbal threat information on the offspring's fear acquisition of novel stimuli may be causal. The current study investigated this verbal fear acquisition pathway from parents to children in the unique context of Covid-19 as a novel environmental threat for parents and children. METHODS: Using an online cross-sectional survey, we collected data about fear of Covid-19, parent-child communication, parental anxiety, and child temperament, in the period between June 11th 2020 and May 28th 2021. Participants were 8 to 18-year-old children (N = 195; Mage = 14.23; 113 girls) and their parents (N = 193; Mage = 47.82; 146 mothers) living in the Netherlands. RESULTS: Children of parents with stronger Covid-19 fears also reported stronger Covid-19 fears. Moreover, parents who were more fearful of Covid-19 provided more threat-related information about the virus to their children. More parental threat information in turn was related to stronger fear of Covid-19 in their children, and partly mediated the link between parent and child fear of the virus. The link between parental threat information and children's fear of Covid-19 was not moderated by child temperament or parental anxiety. CONCLUSIONS: Parental communication about Covid-19 may play a role in children's fear acquisition of Covid-19. The lack of moderation of this link by parental anxiety and child temperament may reflect the potentially adaptive nature of verbal fear transmission during the first year of the pandemic and the nonclinical levels of fear in this community sample.

Information transmission among energy markets, cryptocurrencies, and stablecoins under pandemic conditions

This paper investigates the directional causal relationship and information transmission among the returns of West Texas Intermediate (WTI), Brent, major cryptocurrencies, and stablecoins by drawing on daily data from July 2019 to July 2020. Applying effective transfer entropy, a non-parametric statistic, the results show that the direction of the causal relationship and the nature of information spillovers changed after the COVID-19 pandemic. More precisely, our findings reveal that WTI and Brent are leading the prices of Bitcoin and Bitcoin Cash. Conversely, Bitcoin futures and stablecoins (TrueUSD and USD Coin) are leading WTI and Brent prices. In addition, the stablecoin Tether became a leader against Brent prices after the pandemic, although it is still following WTI prices. Moreover, Ethereum and USD coin preserved their position as leaders against Brent prices. Interestingly, our results also reveal that Ethereum, Litecoin, and Ripple preserved their position as leaders of WTI prices. The change in the nature of directional causality and the spillover effect after the COVID-19 crisis provide valuable information for practitioners, investors, and policymakers on how the ongoing pandemic influences the connection and network correlation among the energy, cryptocurrency, and stablecoin markets. © 2022 Elsevier Inc.

Visualization of the Epidemic Situation of COVID-19

The COVID-19 epidemic has extremely attracted our attentions and lots of maps and visualization charts were created to represent and disseminate the information about COVID-19 in time, which exactly became a key role for the public to acquire and understand the quantitative information and spatial-temporal information of COVID-19. The paper analyzed the dimension of data for COVID-19 and processing levels about them, then divided the COVID-19 visualization into three types, that is 1-order visualization, 2-order visualization and multi-order visualization for COVID-19, based on direct data or indirect data of COVID-19 with the corresponding visualization methods, characteristics and information transmission Shortcomings and weakness of visualization methods for COVID-19 were analyzed in details, from the aspects of multiple scale unit in spatial data statistics, max value dealing in data classification, also many key design points were described including color connotation in disease visualization, the influences of area / unit size in visualization, symbol overlapping, multiple-scale heat maps and labels in statistical tables. The paper indicated the visualization traps of COVID-19, such as misuse of visual effects and excessive visualization, and reasonable abilities of COVID-19 visualization including map-story narrative methods and visualization pertinence for specific problems should be considered sufficiently to provide the references for cartographers to design the maps and for readers to understand the maps. 2021, Science Press. All right reserved.

Quantifying the Influence of Delay in Opinion Transmission of COVID-19 Information Propagation: Modeling Study.

BACKGROUND: In a fast-evolving public health crisis such as the COVID-19 pandemic, multiple pieces of relevant information can be posted sequentially on a social media platform. The interval between subsequent posting times may have a different impact on the transmission and cross-propagation of the old and new information that results in a different peak value and a final size of forwarding users of the new information, depending on the content correlation and whether the new information is posted during the outbreak or quasi-steady-state phase of the old information. OBJECTIVE: This study aims to help in designing effective communication strategies to ensure information is delivered to the maximal number of users. METHODS: We developed and analyzed two classes of susceptible-forwarding-immune information propagation models with delay in transmission to describe the cross-propagation process of relevant information. A total of 28,661 retweets of typical information were posted frequently by each opinion leader related to COVID-19 with high influence (data acquisition up to February 19, 2020). The information was processed into discrete points with a frequency of 10 minutes, and the real data were fitted by the model numerical simulation. Furthermore, the influence of parameters on information dissemination and the design of a publishing strategy were analyzed. RESULTS: The current epidemic outbreak situation, epidemic prevention, and other related authoritative information cannot be timely and effectively browsed by the public. The ingenious use of information release intervals can effectively enhance the interaction between information and realize the effective diffusion of information. We parameterized our models using real data from Sina Microblog and used the parameterized models to define and evaluate mutual attractiveness indexes, and we used these indexes and parameter sensitivity analyses to inform optimal strategies for new information to be effectively propagated in the microblog. The results of the parameter analysis showed that using different attractiveness indexes as the key parameters can control the information transmission with different release intervals, so it is considered as a key link in the design of an information communication strategy. At the same time, the dynamic process of information was analyzed through index evaluation. CONCLUSIONS: Our model can carry out an accurate numerical simulation of information at different release intervals and achieve a dynamic evaluation of information transmission by constructing an indicator system so as to provide theoretical support and strategic suggestions for government decision making. This study optimizes information posting strategies to maximize communication efforts for delivering key public health messages to the public for better outcomes of public health emergency management.

Citizens, doctors, politicians - who´s an expert in times of COVID-19? A survey in Austria and Germany.

BACKGROUND: This study aimed to explore which measures and risk factors for a COVID - 19 infection are considered most important in the general population, health experts and policymakers and to assess the level of agreement across the groups from Austria and Germany. METHODS: A two-phased survey was conducted, participants were matched according to age and gender. Three different groups were asked which measures they considered most relevant in reducing a COVID-19 transmission, to determine which factors contribute most to the risk of disease, and to evaluate the level of agreement in the assessment of risk factor relevance for (a) the transmission of the disease and (b) the risk of a severe course of COVID-19. RESULTS: Risk factors for an infection that were selected from all three groups were immunosuppression/deficiency, cancer, chronic lung disease, smoking, age and working as a health care professional. Interrater agreement per population was only poor to slight and results were highly heterogeneous. CONCLUSIONS: Our survey shows a broad spectrum of opinions and the associated general uncertainty about the risk factors for infection and a severe course of disease across the groups. Profound knowledge of politicians and experts is of high relevance to provide the public with valid information to ensure cooperation fighting the pandemic. TRIAL REGISTRATION: https://apps.who.int/trialsearch/ (ID: DRKS00022166). Registered 15 June 2020.

Linking the disease transmission to information dissemination dynamics: An insight from a multi-scale model study.

During the outbreak of emerging infectious diseases, information dissemination dynamics significantly affects the individuals' psychological and behavioral changes, and consequently influences on the disease transmission. To investigate the interaction of disease transmission and information dissemination dynamics, we proposed a multi-scale model which explicitly models both the disease transmission with saturated recovery rate and information transmission to evaluate the effect of information transmission on dynamic behaviors. Considering time variation between information dissemination, epidemiological and demographic processes, we obtained a slow-fast system by reasonably introducing a sufficiently small quantity. We carefully examined the dynamics of proposed system, including existence and stability of possible equilibria and existence of backward bifurcation, by using the fast-slow theory and directly investigating the full system. We then compared the dynamics of the proposed system and the essential thresholds based on two methods, and obtained the similarity between the basic dynamical behaviors of the slow system and that of the full system. Finally, we parameterized the proposed model on the basis of the COVID-19 case data in mainland China and data related to news items, and estimated the basic reproduction number to be 3.25. Numerical analysis suggested that information transmission about COVID-19 pandemic caused by media coverage can reduce the peak size, which mitigates the transmission dynamics during the early stage of the COVID-19 pandemic.

Evaluation of Distress and Risk Perception Associated with COVID-19 in Vulnerable Groups.

Preventive behavior developed by the population is essential in the face of the risk of coronavirus infection (COVID-19). However, preventive measures will depend on the risk perception acquired. In addition, lockdown can directly affect mental health, provoking distress. Distress could affect risk perception. This study's objective was to analyze whether experiencing distress had an influence on risk perception with respect to vulnerable groups. The sample consisted of 806 participants. The study was conducted during the first week of lockdown declared by the Spanish Government. The Brief Symptom Inventory BSI-18 and a risk perception questionnaire about vulnerable groups was administered. The study revealed the appearance of distress in 9.6% of the sample (85.7% women). Experiencing distress influenced risk perception. This study's main contribution is the link between experiencing distress and the risk perception with respect to vulnerable groups. Risk perception is relevant since it can influence how the population faces the pandemic. Transmission of accurate information could help to minimize the effect of certain cognitive biases that affect risk perception and foster preventive behavior.