ABSTRACT
With nearly 4,500 attendees gathered in San Diego CA, the TMS 2023 Annual Meeting & Exhibition (TMS2023) was the fourth best-attended meeting in TMS history, marking a return to business as usual (more or less) after two decidedly unusual years for the Society's biggest event. By comparison, approximately 2,600 individuals came together in person for TMS2022 in Anaheim CA. One year earlier, TMS2021--held as a fully virtual conference--attracted 2,967 attendees from around the world. This year's event, held Mar 19-23 in one of TMS's most popular meeting locations, brought the conference back closer to its pre-COVID participation numbers. The last time TMS met in San Diego was in 2020 (shortly before widespread pandemic shutdowns began) when more than 4,600 individuals came together for the largest meeting in the Society's history.
ABSTRACT
The COVID-19 pandemic has become a partisan issue rather than an independent public health issue in the US. This study examined the behavioural consequences of motivated reasoning and framing by investigating the impacts of COVID-19 news exposure and news frames, as apparent through a Latent Dirichlet topic modelling analysis of local news coverage, on state-level preventive behaviours as understood through a nationally representative survey. Findings suggested that the media effects on various preventive behaviours differed. The overall exposure rate to all COVID-19 news articles increased mask-wearing but did not significantly impact other preventive behaviours. Four news frames significantly increased avoiding contact or avoiding public or crowded places. However, news articles discussing anxiety and stay at home order triggered resistance and countereffects and led to risky behaviours. ‘Solid Republican' state residents were less likely to avoid contact, avoid public or crowded places, and wear masks. However, partisan leanings did not interfere with the impact of differing local COVID-19 news frames on reported preventive behaviours. Plus, statements regarding pre-existing trust in Trump did not correlate with reported preventive behaviour. Attention to effect sizes revealed that news exposure and news frames could have a bigger impact on health behaviours than motivated reasoning.
ABSTRACT
COVID-19 is a widespread contagious viral infection that can severely affect the respiratory system. Although many people recover from using the disease without special care or treatment, pregnant women are particularly vulnerable to pulmonary infections due to their hangers systems system and physiology. To investigate the treatment provided to pregnant women who are PCR-positive for COVID-19 in their early three months of pregnancy, a reanalyzed analyzed data from 84 participants who received treatment at Tangerang Regional Hospital in 2 study was the study conducted based on an ases of observational investigation with a cross-sectional approach. It assembled the data for analysis of the chi-square test. The results showed that 92.9% of participants underwent a cesarean section, while the remaining 7.1% were discharged after giving birth typically or recovering. Additionally, the study did not find any correlation between factors such as age, education, work, gravida, ANC visit, and the impact of COVID-19 on the third trimester of pregnancy at Tangerang Hospital in 2022. The study recommends that pregnant women seek information about pregnancy care from healthcare providers, particularly midwives, posyandu officers, and the media, to make well-known decisions about their health and well-being during this critical period, ensuring a safe and healthy pregnancy outcome.
ABSTRACT
On social media, misinformation can spread quickly, posing serious problems. Understanding the content and sensitive nature of fake news and misinformation is critical to prevent the damage caused by them. To this end, the characteristics of information must first be discerned. In this paper, we propose a transformer-based hybrid ensemble model to detect misinformation on the Internet. First, false and true news on Covid-19 were analyzed, and various text classification tasks were performed to understand their content. The results were utilized in the proposed hybrid ensemble learning model. Our analysis revealed promising results, establishing the capability of the proposed system to detect misinformation on social media. The final model exhibited an excellent F1 score (0.98) and accuracy (0.97). The AUC (Area Under The Curve) score was also high at 0.98, and the ROC (Receiver Operating Characteristics) curve revealed that the true-positive rate of the data was close to one in this model. Thus, the proposed hybrid model was demonstrated to be successful in recognizing false information online. © 2022 IEEE.
ABSTRACT
Coronavirus disease 2019 (COVID-19) has been admitted by WHO as a global pandemic. The successes-ness in controlling COVID-19 is extremely affected by the knowledge and perception of society. Apothecary students must be competent in carrying out the health promotion effort;one of them is through education. Discovering the impact of education from apothecary students in improving knowledge and perception of the society in controlling COVID-19. One group Quasi-experimental design without a control group (n=102). The data was conducted in March-April 2020 using a validated questionnaire containing the respondents' demographic, knowledge, and perception of COVID-19. This research is 18 years old, does not work as a health worker/medical personnel, domiciled in Yogyakarta, and fills up the pre-test and post-test questionnaire. The data were analyzed descriptively and used the Wilcoxon test (p<0.05) as the statistic test. Most respondents are 52.9% women, 34.31% aged 36-45, with 52.94% having a high school education level. The survey result shows that 71.57% of respondents admit that they know about COVID-19 from television and 2.43% from social media. The answer distribution of questioner on knowledge and perception shows improvements in the pre-test and post-test scores. The Wilcoxon test result, the influence of education on respondents' knowledge and perception, shows the significance of p value=0.000 with the outcome of pre-test and post-test scores with the good category are 67.65% and 5.29%. The presentation of education from apothecary students significantly influences society's knowledge and perception of controlling COVID-19.
ABSTRACT
In the past few years, social media and online news platforms have played an essential role in distributing news content rapidly. Consequently. verification of the authenticity of news has become a major challenge. During the COVID-19 outbreak, misinformation and fake news were major sources of confusion and insecurity among the general public. In the first quarter of the year 2020, around 800 people died due to fake news relevant to COVID-19. The major goal of this research was to discover the best learning model for achieving high accuracy and performance. A novel case study of the Fake News Classification using ELECTRA model, which achieved 85.11% accuracy score, is thus reported in this manuscript. In addition to that, a new novel dataset called COVAX-Reality containing COVID-19 vaccinerelated news has been contributed. Using the COVAX-Reality dataset, the performance of FNEC is compared to several traditional learning models i.e., Support Vector Machine (SVM), Naive Bayes (NB), Passive Aggressive Classifier (PAC), Long Short-Term Memory (LSTM), Bi-directional LSTM (Bi-LSTM) and Bi-directional Encoder Representations from Transformers (BERT). For the evaluation of FNEC, standard metrics (Precision, Recall, Accuracy, and F1-Score) were utilized.
ABSTRACT
The present time brings a lot of controversy and issues on economic, social and political ground. Time did not pass leaving opportunity for taking a breath from the Covid-19 pandemic, because the Ukrainian-Russian war started. This conflict unbalanced the commercial frame of Europe and prices started to go up, inducing reasons for insecurity fear for the wellbeing of tomorrow. Many people started to be anxious, and their symptoms included tachycardia, dyspnea, insomnia, headaches etc. All these symptoms are exacerbated by interfering with news from the media regarding the abovementioned socio-economic problems. Usually women are tented to be more influenceable and more alert, presenting themselves for evaluation in a medical cabinet.
ABSTRACT
The study focuses on the framing of the COVID-19 pandemic in German parliamentary debates and media reports. It concentrates on the first three pandemic waves. The goal is not only to compare political and media framing, but also to show how frames changed from wave to wave. A content analysis of plenary protocols and articles from Welt Online and SZ Online has been carried out, coding single frame elements instead of complete frames, which are instead formed through cluster analyses. Results show that there are differences between government and opposition framing of the pandemic, with the opposition parties criticising the government's crisis management, while the governing parties justified their policies. Concerning the relationship between media and political framing, findings indicate that similar frames are used in both arenas. Nevertheless, differences in frequency are evident. The results show no evidence to support the assumption that frames of the governing parties are picked up more frequently by the media. Moreover, there are no signs of frame alignment between political actors and the media in the early stages of the pandemic nor of a diversification thereafter.
ABSTRACT
Online news and information sources are convenient and accessible ways to learn about current issues. For instance, more than 300 million people engage with posts on Twitter globally, which provides the possibility to disseminate misleading information. There are numerous cases where violent crimes have been committed due to fake news. This research presents the CovidMis20 dataset (COVID-19 Misinformation 2020 dataset), which consists of 1,375,592 tweets collected from February to July 2020. CovidMis20 can be automatically updated to fetch the latest news and is publicly available at: https://github.com/everythingguy/CovidMis20. This research was conducted using Bi-LSTM deep learning and an ensemble CNN+Bi-GRU for fake news detection. The results showed that, with testing accuracy of 92.23% and 90.56%, respectively, the ensemble CNN+Bi-GRU model consistently provided higher accuracy than the Bi-LSTM model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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COVID-19 has crowned a number of other disasters (wildfires in Australia, Desert Locusts in Kenya, an imminent WWIII merging Iran and the US), causing panic to click into place and horror to become our global predicament, making us realize that we live in the illusion of the permanence of things, of mastery, and of immortality. People's turning to social media for trans-local news on COVID-19 has stirred great ire in the world. This led to the proliferation of dark images that associate the viral catastrophe with the end as we know it. To problematize the idea of the apocalypse (or the end) this paper speaks of three moments of survival in human existence: the beneath, the behind and the beyond. We argue that the apocalyptic nature of the pandemic and its global horrorism are part of a congeries of apocalyptic simulations that have always been part of the narrative with which we try to define ourexistence on earth. This paper masks itself against perfunctory examinations of the term apocalypse, and offers instead an understanding that runs along the lines of its Greek etymological sense as apokalyptein (revelation). It offers what Foucault calls an ontology of the present, that interrogates the history of COVID -19 with an emphasis neither on its origin nor on its telos. As beyondists, the COVID-19 catastrophe has revealed to us that 1) we have ‘access to knowledge beyond knowledge' (see Gumpert 2012), and therefore that 2) our modern predicament is not very modern. The end, (not) to be sure, has been lived and relived in the boundary between reality and simulation. After all, the end of something comprises the beginning (in reverse) of that which "endeth”, throwing the beyond, behind and beneath in the Ferris wheel of epistemological and existential entanglement.
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The present study explores the impact of COVID-19 on the volatility structure of the sectoral market in India. ARMA(p,q)- GJR-GARCH(1, 1)-std model is used to determine the daily conditional volatility for 13 selected sectors over the period starting from January 2020 to December 2021. The quantile regression model is employed to examine the changes in the structure of volatility in each sector over the pandemic duration. The results of the study show that the volatility of Metal, Oil–Gas and PSU are more sensitive to market volatility, whereas the volume of new COVID-19 cases exceeds the threshold limit, and no extreme spillover is observed from the market volatility. In addition to this, Bankex, Metal, Oil–Gas, Private Banks and Power sector volatility are more responsive to news sentiments during the period of increase in new COVID-19 cases. Furthermore, the results also reveal that news sentiments help to control the significant fluctuation in the sectoral market. © 2023 MDI.
ABSTRACT
One of the fundamental objectives of higher education is to prepare students to think analytically in order to develop and create knowledge, thus going beyond receiving information and building simple knowledge. That is why higher education must adapt its teaching and learning process to cultivate critical thinking of students. In order for academia to ensure the effectiveness of the development of critical thinking skills, student perceptions cannot be neglected, given that they are the ultimate receptors. In addition, investigating students' perceptions of critical thinking skills could guide future training methods that promote their development. The purpose of this research is to explore students' attitudes and beliefs regarding critical thinking skills, as well as aspects of their development in academia and their transfer to other contexts. The study is conducted at the Dunarea de Jos University of Galaţi and uses the questionnaire survey method to assess students' perceptions of critical thinking, from several perspectives: the level of knowledge on critical thinking skills, strategies for learning critical thinking skills, the qualities of a critical thinker, the way students relate to the COVID 19 pandemic and fake news. To obtain the necessary data, the questionnaire was distributed through Microsoft Forms and subsequently analyzed to describe students' views on critical thinking. A sample of 101 students from specializations in the field of socio-humanities completed this survey. The results of the study showed that students invoke the need to overcome difficulties in developing critical thinking skills by: training teachers to use critical thinking in the classroom;including and practicing critical thinking skills in applied activities at courses and seminars;applying debates and discussions in the classroom as teaching and learning strategies;translating the theories learned in courses into different case studies;use of training skills, questionnaires, homework;participation in group projects in a collaborative environment. [ FROM AUTHOR] Copyright of Romanian Journal for Multidimensional Education / Revista Romaneasca pentru Educatie Multidimensionala is the property of Lumen Publishing House and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Rudy Gobert's positive COVID-19 diagnosis in March of 2020 started the process that led to American sports shutting down in the early days of the pandemic. After the diagnosis, video of him touching reporters' voice recorders at a press availability went viral. This framing analysis in five mainstream newspapers finds that over the course of 72 hours, Gobert went from a bad actor to a hero in news copy as an episodic frame focusing on his actions gave way to a thematic frame about the virus and its effects on the country.
ABSTRACT
This study examined the mechanisms through which responsibility frames and stigmatizing headlines influence support for governmental policies to address the pandemic. Based on a factorial design experiment, we examined the effects of 2 responsibility frames (individual vs. societal responsibility) and 4 headline types (non-stigmatized vs. name-stigmatized vs. characteristic-stigmatized vs. both-stigmatized). The results showed that the individual responsibility frame increased individual attribution of responsibility for the cause and spread of COVID-19 whereas reducing societal attribution of responsibility, compared to the societal responsibility frame. The headline that detailed both the stigmatized characteristic and name increased individual attribution of responsibility compared to the non-stigmatized headline. Furthermore, the effects of frames and headline types on policy support were sequentially mediated by attribution of responsibility and emotions. Individual attribution of responsibility led to anger whereas societal attribution of responsibility led to sympathy. Subsequently, anger increased support for punitive policies while sympathy increased support for assistive policies. This study contributes to the literature on news framing of pandemics by integrating cognitive and emotional mechanisms in forming policy attitudes. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
This paper explores the phenomenon of fake news and conspiracy theories during the COVID-19 pandemic in Germany with special focus on the emergence of the Querdenker movement. Through a post-structuralist lens complemented by the work of Michel Foucault, the concept of truth will be analyzed to understand its role in society and democratic discourse as well as how the production of knowledge and truth has changed with emergence of the internet and social media. In this context it becomes apparent how fake news can be threatening to political discourse by undermining basic scientific information necessary for effective decision-making processes. Insights of this analysis will then be used to develop legal propositions to tackle the problem of fake news without interfering too much with the determination of truth and public discourse. © 2022, Onati International Institute for the Sociology of Law. All rights reserved.
ABSTRACT
Featured ApplicationThe research has a potential application in the field of fake news detection. By using the feature extraction technique, TwIdw, proposed in this paper, more relevant and informative features can be extracted from the text data, which can lead to an enhancement in the accuracy of the classification models employed in these tasks.This research proposes a novel technique for fake news classification using natural language processing (NLP) methods. The proposed technique, TwIdw (Term weight–inverse document weight), is used for feature extraction and is based on TfIdf, with the term frequencies replaced by the depth of the words in documents. The effectiveness of the TwIdw technique is compared to another feature extraction method—basic TfIdf. Classification models were created using the random forest and feedforward neural networks, and within those, three different datasets were used. The feedforward neural network method with the KaiDMML dataset showed an increase in accuracy of up to 3.9%. The random forest method with TwIdw was not as successful as the neural network method and only showed an increase in accuracy with the KaiDMML dataset (1%). The feedforward neural network, on the other hand, showed an increase in accuracy with the TwIdw technique for all datasets. Precision and recall measures also confirmed good results, particularly for the neural network method. The TwIdw technique has the potential to be used in various NLP applications, including fake news classification and other NLP classification problems.
ABSTRACT
Existing deep learning-based methods for detecting fake news are uninterpretable, and they do not use external knowledge related to the news. As a result, the authors of the paper propose a graph matching-based approach combined with external knowledge to detect fake news. The approach focuses on extracting commonsense knowledge from news texts through knowledge extraction, extracting background knowledge related to news content from a commonsense knowledge graph through entity extraction and entity disambiguation, using external knowledge as evidence for news identification, and interpreting the final identification results through such evidence. To achieve the identification of fake news containing commonsense errors, the algorithm uses random walks graph matching and compares the commonsense knowledge embedded in the news content with the relevant external knowledge in the commonsense knowledge graph. The news is then discriminated as true or false based on the results of the comparative analysis. From the experimental results, the method can achieve 91.07%, 85.00%, and 89.47% accuracy, precision, and recall rates, respectively, in the task of identifying fake news containing commonsense errors.
ABSTRACT
As the Covid-19 pandemic progressed, the public increasingly relied on news outlets to provide up-to-date health information. Often times this information was provided by Dr. Anthony Fauci during the course of on-air interviews. Consequently, when Dr. Fauci appeared less and less, many became concerned that the public was not receiving the full picture, especially since Dr. Fauci was often not afraid to voice concerns over how the pandemic was being handled at the federal, state and local level. Using text and image data from 6,587 CNN, Fox News and MSNBC programs, this paper determines the extent to which Dr. Fauci appeared on air and whether the rate of his appearances (or lack thereof) diminished over time. We then look at whether Dr. Fauci's appearances (or lack thereof) are conditioned on what is being said during broadcasts. Not only do we find that Dr. Fauci appeared significantly less on Fox News, but this discrepancy increases as the pandemic progresses and when public health information is discussed. Regardless of whether this constitutes "misinformation” or "framing,” our study speaks volumes to two important research areas and broader concerns over the balance of Covid-19 coverage, especially when the public needed it the most. © Bryce J. Dietrich & Hyein Ko.
ABSTRACT
In a rapidly developing crisis such as the COVID-19 pandemic, people are often faced with contradictory or changing information and must determine what sources to trust. Across five time points (N = 5902) we examine how trust in various sources predicts COVID-19 health behaviors. Trust in experts and national news predicted more engagement with most health behaviors from April 2020 to March 2022 and trust in Fox news, which often positioned itself as counter to the mainstream on COVID-19, predicted less engagement. However, we also examined a particular public health behavior (masking) before and after the CDC announcement recommending masks on 3 April 2020 (which reversed earlier expert advice discouraging masks for the general public). Prior to the announcement, trust in experts predicted less mask-wearing while trust in Fox News predicted more. These relationships disappeared in the next 4 days following the announcement and reversed in the 2 years that follow, and emerged for vaccination in the later time points. We also examine how the media trusted by Democrats and Republicans predicts trust in experts and in turn health behaviors. Broadly we consider how the increasingly fragmented epistemic environment has implications for polarization on matters of public health. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
This chapter examines the role of COVID-19 fake news disseminated on social media platforms (Twitter, Facebook and WhatsApp) in Zimbabwe. The research was guided by three research questions: (1) What is the nature of COVID-19 fake news in Zimbabwe? (2) How have Zimbabweans responded to the fake news? (3) What are the consequences of the fake news to COVID-19 response efforts? The study provided answers to these questions via a Fake News Receptivity Test (FNRT) and a sample population of one hundred and seventy-three social media users drawn from Harare-Zimbabwe's capital. The research discovered that 82% of the sample population accepted the COVID-19 fake news as truth. Drawing from these findings, the paper maintains that the rapid spread and controversy surrounding the COVID-19 pandemic in Zimbabwe can also be attributed to the role of fake news. The fake news mainly manifests in the form of false information about the pandemic, erroneous medical advice, fraudulent preventive measures and scandalous rumours about COVID-19 vaccines. The study concluded that the widespread acceptance of COVID-19 fake news in Zimbabwe has resulted in low vaccination turnout, flouting of COVID-19 safety protocols and the spiking of COVID-19-related deaths and infections. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.