ABSTRACT
During the COVID-19 pandemic, self-proclaimed resistance movements have organized protests against containment measures both in digital media and on the streets. References to the past and an invocation of collective memory have been important elements in the toolbox of their populist communication. We propose the notion of "commemorative populism" to describe the weaponization of history and memory for the proliferation of a political cause by populist activists. In a qualitative content analysis, we examined postings by the German "Querdenker," a movement against Corona containment policies. Findings show 6 types of the (ab)use of history and collective memory: (1) the recontextualization of quotations by historical personalities, (2) the creation of false historical analogies and flattering genealogies, (3) the claim of historical exceptionalism, (4) the denigration of elites by referring to failures of medical history, (5) the dissemination of disinformation about historical facts, and (6) the support of conspiracy myths by the myths' own history.
ABSTRACT
The global pandemic caused by Covid-19 has led to the fact that more than 1.8 billion children and young people around the world found themselves outside the classroom education process. This prompted the expansion of digitization processes, the search for effective solutions to support remote educational interaction, which is reflected in articles of the American, Malaysian, Spanish, Iranian, Ukrainian, etc. scientists The analysis of foreign experience proved the interest of the world educational community in the introduction of mobile services, messengers, in particular the Telegram messenger, as a tool for supporting the educational process. The article examines the problem of using the Telegram messenger to support the educational process in higher education institution in the conditions of quarantine restrictions caused by the global Covid-19 pandemic. Modern messengers, in particular Telegram, Viber, Facebook Messenger, WhatsApp, are analyzed due to criteria (commerciality, functionality, architecture, security) and indicators. The advantages of using the Telegram messenger to support the educational process are outlined, in particular: cross-platform, support for synchronous and asynchronous interaction, the ability to exchange messages in different formats, support for various types of interaction, the ability to ensure the fulfillment of many pedagogical tasks. The essence, advantages and possibilities of using the chatbot tool from the Telegram messenger are described. The psychological and pedagogical recommendations for increasing the pedagogical effect of using the Telegram chatbot are provided. The educational interaction results after using the Telegram messenger were analyzed (survey of 112 students, learning results evaluation in the experimental (112 persons) and control (110 persons) student groups). The empirical research shows that the Telegram messenger allows supporting the educational process in the conditions of quarantine restrictions, with saving quality indicators, as well as achieving pedagogical goals.
ABSTRACT
This research hypothesizes that all conspiracy theories have dominating isotopies and images‐symbols regardless of ideology or context. As a result, I hypothesized that the common denominator might be discovered in figurative reasoning, which means using the same representations to explain current events, in order to detect an ideal center of the seman-tic universe of conspiracy where the diverse conspiracist fringes converge. Social media invariant topicalizations of the Covid‐19 epidemic and the Russia–Ukraine war are the ideal field to validate this hypothesis. The corpus on which the study was conducted consists of thousands of online items published between February 15, 2020, and October 15, 2022. Within the corpus were chosen posts by QAnon supporters designated as disinformation "superspreaders.”. © 2023 by the author(s);licensee Cogitatio Press (Lisbon, Portugal). TAttribution 4.0 International License (CC BY).
ABSTRACT
Throughout the COVID-19 pandemic, conspiracy beliefs about the virus spread quickly. Using an online-representative survey in Germany, this study examines the rela-tionship between such conspiracy beliefs and media use with special regard to alternative media and influencers as well as social media. Instead of aggregating different social media platforms, this study identifies differences between them. The results show that COVID-19 conspiracy beliefs are positively associated with the use of Telegram. The use of alternative media, Facebook, and YouTube shows only very weak positive associations. On the other hand, exposure to journalistic media is negatively associated with conspiracy beliefs. Cau-salities and implications of these findings are discussed.
ABSTRACT
The paper presents the outcomes of AI-COVID19, our project aimed at better understanding of misinformation flow about COVID-19 across social media platforms. The specific focus of the study reported in this paper is on collecting data from Telegram groups which are active in promotion of COVID-related misinformation. Our corpus collected so far contains around 28 million words, from almost one million messages. Given that a substantial portion of misinformation flow in social media is spread via multimodal means, such as images and video, we have also developed a mechanism for utilising such channels via producing automatic transcripts for videos and automatic classification for images into such categories as memes, screenshots of posts and other kinds of images. The accuracy of the image classification pipeline is around 87%.
ABSTRACT
Research has explored how the COVID-19 pandemic triggered a wave of conspiratorial thinking and online hate speech, but little is empirically known about how different phases of the pandemic are associated with hate speech against adversaries identified by online conspiracy communities. This study addresses this gap by combining observational methods with exploratory automated text analysis of content from an Italian-themed conspiracy channel on Telegram during the first year of the pandemic. We found that, before the first lockdown in early 2020, the primary target of hate was China, which was blamed for a new bioweapon. Yet over the course of 2020 and particularly after the beginning of the second lockdown, the primary targets became journalists and healthcare workers, who were blamed for exaggerating the threat of COVID-19. This study advances our understanding of the association between hate speech and a complex and protracted event like the COVID-19 pandemic, and it suggests that country-specific responses to the virus (e.g., lockdowns and re-openings) are associated with online hate speech against different adversaries depending on the social and political context.
ABSTRACT
During the Covid-19 pandemic, there was an increase in the use of electrical energy on a household scale. This study developed a home-scale power monitoring system to monitor electrical power at a household scale. This research was conducted to facilitate access to home power monitoring via Android based on the Internet of Things using the Thinger.IO web browser and Telegram Messenger using the Bot feature. This power monitoring system develops using the ACS712 sensor as a current reader and the ZMPT101B as a voltage reader, using an ESP32 microcontroller with a WiFi module that can be connected online. The results of this study are that the accuracy of the ZMPT101B voltage sensor is excellent, with an accuracy value of 99.845%. The ACS712 current sensor has the highest difference value with a reference of 0.32 A and 0.04 A for the lowest difference value. The data logger system on Thinger.IO works well in recording data. The Bot Feature on the Telegram application can work well even though it has an average delay of up to 4.2 seconds, depending on the speed of the internet network. © 2022 IEEE.
ABSTRACT
The Querdenken movement, the leading force behind German corona protests, is suspected of being a gateway to far-right attitudes due to radicalizing inward-oriented communication on Telegram. To investigate potential connections of this movement to the far right and alternative media—and to explore key topics of the Querdenken network over time—we analyzed 6,294,955 messages from 578 public Telegram channels via network analysis and structural topic modeling. This analysis revealed that Querdenken's subcommunities preferably forward content from far-right and QAnon communities, while far-right and conspiracy theorist alternative media channels act as content distributors for the movement. Four main topics appeared in the Querdenken network with varying prevalence over time and across different communities: promotion, QAnon, right-wing populism, and COVID-19 conspiracy theories. Our results highlight potential directions for future research and practical implications, for example, that political decision makers should account for the increasing influence of the QAnon movement on Querdenken mobilizers' Telegram activity. © The Author(s) 2023.
ABSTRACT
In this paper, we propose a model named Virtual Doctor- Teleconsultation and Parameter Monitoring System' which provides some usefulness of providing medication and helps in gauging the essential parameters (Heart rate, Temperature and SpO2) and UVC (Ultraviolet sort C) sterilization unit for the sensors. During the ongoing situation, diminishing the human-to-human contact in emergency clinics is required. In a bid, to keep specialists and clinical staff from getting impacted by Coronavirus, the job of medication conveying robots are being developed. We can attain the Locomotion procedure of the robot using telegram bot and live video streaming by ESP32-Camera. The working principle is that the Doctor or the Nurse can control the moment of entire model by observing surroundings using a camera and commanding through a mobile application. For this model, we are utilizing the essential microcontroller, that is to say, Arduino UNO. We were effective in taking readings with the assistance of a sensors and had the option to supply capacity to the UVC light in which it cleaned the articles inside the unit when it was uncovered for 2-3 minutes. Lastly, the robot had the option to move effectively with the assistance of Arduino and Wi-Fi arrangement. All the data will be successfully sent to the Doctor's smartphone using Telegram application and NodeMCufor internet connectivity. © 2022 IEEE.
ABSTRACT
During the Covid-19 pandemic, there was an increase in the use of electrical energy on a household scale. This study developed a home-scale power monitoring system to monitor electrical power at a household scale. This research was conducted to facilitate access to home power monitoring via Android based on the Internet of Things using the Thinger.IO web browser and Telegram Messenger using the Bot feature. This power monitoring system develops using the ACS712 sensor as a current reader and the ZMPT101B as a voltage reader, using an ESP32 microcontroller with a WiFi module that can be connected online. The results of this study are that the accuracy of the ZMPT101B voltage sensor is excellent, with an accuracy value of 99.845%. The ACS712 current sensor has the highest difference value with a reference of 0.32 A and 0.04 A for the lowest difference value. The data logger system on Thinger.IO works well in recording data. The Bot Feature on the Telegram application can work well even though it has an average delay of up to 4.2 seconds, depending on the speed of the internet network. © 2022 IEEE.
ABSTRACT
Self-isolation is step or effort to stop the spread of the Covid-19 virus that can carried out by individuals infected with the corona virus. However, they do not show enough symptoms seriously. This is one method to push amount Covid-19 cases. People who do self-isolation must stay at home around 7 days until they are free from Covid-19. To help monitoring by effective condition patient in self-isolation at home and reduce risk the symptoms of Covid-19 experienced, it requires a support system. In this research, it makes a system that can help inhabitant of village to monitor condition patients in the room during self-isolation through camera-based detection object and some sensors to monitor their health such as temperature, heart rate, and oxygen saturation. Camera can classify condition patient based on real-time video recording. If patient is detected lie down or fall on the floor, it will be assumed need help and message emergency sent to the telegram bot. However, if the patient is in a position like stand up, it will be assumed that patient in health condition. By using Mobilenet V2 320x320 SSD object model the average of accuracy is obtained by 86.8%. The results in this system could be monitored through web page. © 2022 IEEE.
ABSTRACT
The paper presents the outcomes of AI-COVID19, our project aimed at better understanding of misinformation flow about COVID-19 across social media platforms. The specific focus of the study reported in this paper is on collecting data from Telegram groups which are active in promotion of COVID-related misinformation. Our corpus collected so far contains around 28 million words, from almost one million messages. Given that a substantial portion of misinformation flow in social media is spread via multimodal means, such as images and video, we have also developed a mechanism for utilising such channels via producing automatic transcripts for videos and automatic classification for images into such categories as memes, screenshots of posts and other kinds of images. The accuracy of the image classification pipeline is around 87%. © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.
ABSTRACT
BACKGROUND: The 2019 novel COVID-19 has severely burdened the health care system through its rapid transmission. Mobile health (mHealth) is a viable solution to facilitate remote monitoring and continuity of care for patients with COVID-19 in a home environment. However, the conceptualization and development of mHealth apps are often time and labor-intensive and are laden with concerns relating to data security and privacy. Implementing mHealth apps is also a challenging feat as language-related barriers limit adoption, whereas its perceived lack of benefits affects sustained use. The rapid development of an mHealth app that is cost-effective, secure, and user-friendly will be a timely enabler. OBJECTIVE: This project aimed to develop an mHealth app, DrCovid+, to facilitate remote monitoring and continuity of care for patients with COVID-19 by using the rapid development approach. It also aimed to address the challenges of mHealth app adoption and sustained use. METHODS: The Rapid Application Development approach was adopted. Stakeholders including decision makers, physicians, nurses, health care administrators, and research engineers were engaged. The process began with requirements gathering to define and finalize the project scope, followed by an iterative process of developing a working prototype, conducting User Acceptance Tests, and improving the prototype before implementation. Co-designing principles were applied to ensure equal collaborative efforts and collective agreement among stakeholders. RESULTS: DrCovid+ was developed on Telegram Messenger and hosted on a cloud server. It features a secure patient enrollment and data interface, a multilingual communication channel, and both automatic and personalized push messaging. A back-end dashboard was also developed to collect patients' vital signs for remote monitoring and continuity of care. To date, 400 patients have been enrolled into the system, amounting to 2822 hospital bed-days saved. CONCLUSIONS: The rapid development and implementation of DrCovid+ allowed for timely clinical care management for patients with COVID-19. It facilitated early patient hospital discharge and continuity of care while addressing issues relating to data security and labor-, time-, and cost-effectiveness. The use case for DrCovid+ may be extended to other medical conditions to advance patient care and empowerment within the community, thereby meeting existing and rising population health challenges.
ABSTRACT
Currently the world is being reported with the emergence of a new virus, namely the Covid-19 virus, so the Indonesian government implements a Health protocol in the form of Physical Distancing. However, as time goes by, the government recommends that we get used to what is going on, one example is starting to allow on-site teaching and learning activities but on the condition that we continue to implement the existing protocol, namely implementing Physical Distancing. Through the design of this tool, namely smart presence using RFID and ultrasonic sensors based on the Internet Of Things (IoT) by paying attention to the object distance <50 cm which then sends a notification to the Telegram application when the object distance is less than 50 cm and the attendance status is successful. After testing is carried out on all components of the tool, all systems that have been made can work and function properly in accordance with the desired system design. It is hoped that the system created can make it easier for students to apply Physical Distancing health protocols in classroom learning activities and add insight into the importance of maintaining health. © 2022 Institute of Advanced Engineering and Science (IAES).
ABSTRACT
For the last two years, the world has been fighting an invisible enemy: COVID-19 (coronavirus). The spreading of this virus caused an unprecedented pandemic, bringing out some critical health system issues due to overcrowded hospitals and undersized medical personnel compared to the number of infected. Indeed, in this context, health facilities have proven inadequate in treating COVID-19 patients who were in quarantine at home, leading to overcrowded hospitals. An efficient home monitoring system would have reserved hospital beds for patients in severe conditions while, at the same time, doctors would have followed up on patients who had mild disease symptoms remotely. Unfortunately, the development of telemedicine was not enough;devices were not user-friendly and had insufficient memory to guarantee daily data storage. ROH-BOT is an IoT device that allows real-Time contact with the doctor, tracking the patient's vital values, and registers the critical parameters that characterize the specific disease. It also allows quick contact with a trusted third person due to its association with a Telegram bot. Moreover, thanks to its user-friendly characteristics, ROH-BOT increases the growing digitalization in the medical field and the democratization of medical technology. In this way, ROH-BOT aims to solve the difficulties related to home monitoring relieved during the pandemic. © 2022 IEEE.
ABSTRACT
"2020 went down in history as the year of the pandemic and lockdowns. In the context of self-isolation, the construction of a global media event, the COVID-19 pandemic, plays a key role in the audience's perception of information and their further actions. The research focuses on the timeline of the ""first wave"" of the spread of the virus (the initial stage, the implementing of compulsory universal self-isolation, the lifting of restrictive measures). Six social and political Telegram channels with a large outreach, which often served as a key source of information about the pandemic for the public, were chosen for the analysis. In total, 825 posts were analysed. The main sources of information about the coronavirus were identified: the media, official data from organizations that keep statistics on people who got infected/recovered, statements by officials on the situation in a country and the world, and the Telegram channels' own information. During the pandemic, popular Telegram channels adhered to a common agenda alongside with the media, thus, in fact, not offering a large percentage of original materials. Based on the content analysis, a conclusion is made about the transformation of the construction of a media event. In terms of visualization, posts containing photos or emojis predominated. By the end of the first wave, the number of posts containing videos dropped. Short clips (up to 20-30 seconds), in fact, served as photo illustrations. The increase in the number of posts containing memes is explained by the need for a mass audience to understand and reflect on the events that are taking place. During the ""first wave"", the priority areas in the topics of the posts were statistics on the number of infected/recovered people;initiatives of the authorities;and social, cultural, and entertainment subject matters. However, from the initial period to the moment when self-isolation was lifted, the topics of the posts changed: the number of articles on morbidity and mortality significantly decreased, the second period recorded the largest number of articles about lifestyle, while social topics were among the leading ones in the third period. The study revealed a miniscule number of fake news - 1%, which can be explained by the tightening of criminal legislation regarding the dissemination of knowingly false information. Regarding the theory of strategies for deproblematization of situations, the Telegram channels used the following strategies: the strategy of declaring powerlessness, the strategy of perspectivization, and the strategy of criticizing tactics."
ABSTRACT
The COVID-19 pandemic led to the creation of a new protest movement, positioned against government lockdowns, mandatory vaccines, and related measures. Efforts to control misinformation by digital platforms resulted in take downs of key accounts and posts. This led some of these protest groups to migrate to platforms with less stringent content moderation policies, such as Telegram. Telegram has also been one of the destinations of the far right, whose deplatforming from mainstream platforms began a few years ago. Given the co-existence of these two movements on Telegram, the article examines their connections. Empirically, the article focused on Irish Telegram groups and channels, identifying relevant protest movements and collecting their posts. Using computational social science methods, we examine whether far-right terms and discourses are present and how this varies across different clusters of Telegram Covid-19 protest groups. In addition, we examine which actors are posting far-right content and what kind of roles they play in the network of Telegram groups. The findings indicate the presence of far-right discourses among the COVID-19 groups. However, the existence of these groups was not solely driven by the extreme right, and the incidence of far-right discourses was not equal across all COVID-19 protest groups. We interpret these findings under the prism of the mediation opportunity structure: while the far right appears to have taken advantage of the network opportunity structure afforded by deplatforming and the migration to Telegram, it did not succeed in diffusing its ideas widely among the COVID-19 protest groups in the Irish Telegram.
ABSTRACT
Online communities play an important role in spreading public discontent and could contribute to polarization. This study focuses on anti-vaccination views in the Netherlands, which have intensified during the COVID-19 pandemic. We examined the structure and development of five Dutch anti-vaccination Telegram groups and studied their interactivity and posting behaviour. Using group-based trajectory modelling, we examined the development of users’ posting behaviour in these groups. We find four posting trajectories across all five groups. A small group of users contributes the majority of posts. Overall, posting frequency declines over time and our results do not show evidence for a group of users whose posting frequency increases. This is taken to indicate that only a small group of users spread their anti-vaccination views through Telegram groups. While social media can reach a broad audience, most users are not necessarily engaged to also actively contribute to the online anti-vaccination community. [ FROM AUTHOR] Copyright of New Media & Society is the property of Sage Publications, Ltd. 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
The article is devoted to the problem of using Telegram messenger in the educational process in supporting the higher school under the conditions of forced quarantine restrictions due to the Covid-19 pandemic. Modern messengers (Telegram, Viber, Facebook Messenger, WhatsApp) are analyzed via pre-defined criteria (commerciality, functionality, architecture, security) and the range of indicators, the benefits of using Telegram messenger to support the educational process are outlined. The essence, benefits, and possibilities of using Telegram ChatBot are characterized. The main steps for creating Telegram ChatBot are described. Recommendations are provided to improve the pedagogical effect of using Telegram ChatBots. The analysis of results of educational interaction via Telegram messenger is presented (112 students’ survey, evaluation of learning outcomes in experiment (112 students) and control (110 students) groups). The empirical research has shown that Telegram messenger allowed supporting the educational process in the conditions of unexpected and forced quarantine restrictions, with no loss of qualitative indicators, achieving the pedagogical goals. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
BACKGROUND: The COVID-19 pandemic has disrupted medical education, shifting learning online. Social media platforms, including messaging apps, are well integrated into medical education. However, Telegram's role in medical education remains relatively unexplored. OBJECTIVE: This study aims to explore the perceptions of medical students regarding the role of messaging apps in medical education and their experience of using Telegram for surgical education. METHODS: A Telegram channel "Telegram Education for Surgery Learning and Application (TESLA)" was created to supplement medical students' learning. We invited 13 medical students who joined the TESLA channel for at least a month to participate in individual semistructured interviews. Interviews were conducted via videoconferencing using an interview guide and were then transcribed and analyzed by 2 researchers using inductive thematic content analysis. RESULTS: Two themes were identified: (1) learning as a medical student and (2) the role of mobile learning (mLearning) in medical education. Students shared that pandemic-related safety measures, such as reduced clinic allocations and the inability to cross between wards, led to a decrease in clinical exposure. Mobile apps, which included proprietary study apps and messaging apps, were increasingly used by students to aid their learning. Students favored Telegram over other messaging apps and reported the development of TESLA as beneficial, particularly for revision and increasing knowledge. CONCLUSIONS: The use of apps for medical education increased during the COVID-19 pandemic. Medical students commonly used apps to consolidate their learning and revise examination topics. They found TESLA useful, relevant, and trustworthy.