Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userPartisanship and Fear are Associated with Resistance to COVID-19 Directives
ترتبط الحزانة والخوف بمقاومة توجيهات CovID-19
230
0 0
0.0
(
0
)
Created by
Shamra Editor
Ask ChatGPT about the research
كانت الاختلافات الأيديولوجية لها تأثير كبير على الاستجابة الفردية والمجتمعية لوباء Covid-19 في الولايات المتحدة.أظهرت الأبحاث السلوكية المبكرة خلال الوعاء أن المحافظين كانوا أقل عرضة للالتزام بالتوجيهات الصحية، مما يتناقض مع مجموعة عمل يشير إلى أن الأيديولوجية المحافظة تؤكد على قاعدة مستمرة، نفور الخسائر، والوقاية.نحن نتوقف مع هذا التناقض من خلال تحليل المحتوى الدلالي للإصدارات الصحفية المحلية والإصدارات الصحفية الفيدرالية والتغريدات المحلية خلال الشهر الأول من الاستجابة الحكومية إلى Covid-19 في الولايات المتحدة.السيطرة على العوامل مثل الحالات والوفيات المؤكدة Covid-19 المؤكدة والمؤشرات الاقتصادية المحلية، وأكثر من ذلك، نجد أن التعبيرات عبر الإنترنت من الخوف في المناطق المحافظة تؤدي إلى زيادة في الالتزام بتوصيات الصحة العامة فيما يتعلق بالكوفي - 19، وأن تعبيرات الخوففي البيانات الصحفية الحكومية هي مؤشر كبير للخوف المعبر عنه على تويتر.
Ideological differences have had a large impact on individual and community response to the COVID-19 pandemic in the United States. Early behavioral research during the pandemic showed that conservatives were less likely to adhere to health directives, which contradicts a body of work suggesting that conservative ideology emphasizes a rule abiding, loss aversion, and prevention focus. We reconcile this contradiction by analyzing semantic content of local press releases, federal press releases, and localized tweets during the first month of the government response to COVID-19 in the United States. Controlling for factors such as COVID-19 confirmed cases and deaths, local economic indicators, and more, we find that online expressions of fear in conservative areas lead to an increase in adherence to public health recommendations concerning COVID-19, and that expressions of fear in government press releases are a significant predictor of expressed fear on Twitter.
References used
https://aclanthology.org/
rate research
Read More
In this paper, we present ArCOV-19, an Arabic COVID-19 Twitter dataset that spans one year, covering the period from 27th of January 2020 till 31st of January 2021. ArCOV-19 is the first publicly-available Arabic Twitter dataset covering COVID-19 pan
demic that includes about 2.7M tweets alongside the propagation networks of the most-popular subset of them (i.e., most-retweeted and -liked). The propagation networks include both retweetsand conversational threads (i.e., threads of replies). ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing. Preliminary analysis shows that ArCOV-19 captures rising discussions associated with the first reported cases of the disease as they appeared in the Arab world.In addition to the source tweets and the propagation networks, we also release the search queries and the language-independent crawler used to collect the tweets to encourage the curation of similar datasets.
This paper presents the preliminary results of an ongoing project that analyzes the growing body of scientific research published around the COVID-19 pandemic. In this research, a general-purpose semantic model is used to double annotate a batch of 5
00 sentences that were manually selected from the CORD-19 corpus. Afterwards, a baseline text-mining pipeline is designed and evaluated via a large batch of 100,959 sentences. We present a qualitative analysis of the most interesting facts automatically extracted and highlight possible future lines of development. The preliminary results show that general-purpose semantic models are a useful tool for discovering fine-grained knowledge in large corpora of scientific documents.
Conversational Agents (CAs) can be a proxy for disseminating information and providing support to the public, especially in times of crisis. CAs can scale to reach larger numbers of end-users than human operators, while they can offer information int
eractively and engagingly. In this work, we present Theano, a Greek-speaking virtual assistant for COVID-19. Theano presents users with COVID-19 statistics and facts and informs users about the best health practices as well as the latest COVID-19 related guidelines. Additionally, Theano provides support to end-users by helping them self-assess their symptoms and redirecting them to first-line health workers. The relevant, localized information that Theano provides, makes it a valuable tool for combating COVID-19 in Greece. Theano has already conversed with different users in more than 170 different conversations through a web interface as a chatbot and over the phone as a voice bot.
We present a COVID-19 news dashboard which visualizes sentiment in pandemic news coverage in different languages across Europe. The dashboard shows analyses for positive/neutral/negative sentiment and moral sentiment for news articles across countrie
s and languages. First we extract news articles from news-crawl. Then we use a pre-trained multilingual BERT model for sentiment analysis of news article headlines and a dictionary and word vectors -based method for moral sentiment analysis of news articles. The resulting dashboard gives a unified overview of news events on COVID-19 news overall sentiment, and the region and language of publication from the period starting from the beginning of January 2020 to the end of January 2021.
To combat COVID-19, both clinicians and scientists need to digest the vast amount of relevant biomedical knowledge in literature to understand the disease mechanism and the related biological functions. We have developed a novel and comprehensive kno
wledge discovery framework, COVID-KG to extract fine-grained multimedia knowledge elements (entities, relations and events) from scientific literature. We then exploit the constructed multimedia knowledge graphs (KGs) for question answering and report generation, using drug repurposing as a case study. Our framework also provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence. All of the data, KGs, reports.
suggested questions
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
