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      Study on the communication effect of the social livestream of cabin hospitals' construction process during the COVID-19 outbreak

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          Abstract

          When the world is recovering from the chaos that COVID-19 creates, the epidemic is still posing challenges to the public health system and communication. However, a case of information communication during the COVID-19 outbreak can provide a reference for the current information promulgate strategy in China. In January 2020, CCTV broadcasted the construction of two cabin hospitals on a 24-h Livestream (24H-LS), creating a remarkable viewing effect. We conducted a quantitative analysis based on the number of views, social media communication, and internet search index. We collected posts and comment data of the 24H-LS audience and related topics on Weibo, using sentiment classification and word frequency analysis to study the communication effect of 24H-LS from three perspectives: perception effect, psychology, and subject issue. The results show that, first, 24H-LS has attracted extensive public attention on the Internet and social media after its launch. Second, the public's perception of the risks of the COVID-19 outbreak and its uncertainty has decreased after watching the 24H-LS. At the same time, the positive emotions of the public have been enhanced to a certain extent. Third, through subject analysis, we found that the public had high participation and strong interaction in 24H-LS, which produced collective symbols and emotions. The study shows that through 24H-LS, a new information form, the media can effectively convey important information and resolve the public's fear and anxiety.

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          Most cited references29

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          An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China

          Responding to an outbreak of a novel coronavirus (agent of COVID-19) in December 2019, China banned travel to and from Wuhan city on 23 January and implemented a national emergency response. We investigated the spread and control of COVID-19 using a unique data set including case reports, human movement and public health interventions. The Wuhan shutdown was associated with the delayed arrival of COVID-19 in other cities by 2.91 days (95%CI: 2.54-3.29). Cities that implemented control measures pre-emptively reported fewer cases, on average, in the first week of their outbreaks (13.0; 7.1-18.8) compared with cities that started control later (20.6; 14.5-26.8). Suspending intra-city public transport, closing entertainment venues and banning public gatherings were associated with reductions in case incidence. The national emergency response appears to have delayed the growth and limited the size of the COVID-19 epidemic in China, averting hundreds of thousands of cases by 19 February (day 50).
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            BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

            We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly conditioning on both left and right context in all layers. As a result, the pre-trained BERT model can be fine-tuned with just one additional output layer to create state-of-the-art models for a wide range of tasks, such as question answering and language inference, without substantial task-specific architecture modifications. BERT is conceptually simple and empirically powerful. It obtains new state-of-the-art results on eleven natural language processing tasks, including pushing the GLUE score to 80.5% (7.7% point absolute improvement), MultiNLI accuracy to 86.7% (4.6% absolute improvement), SQuAD v1.1 question answering Test F1 to 93.2 (1.5 point absolute improvement) and SQuAD v2.0 Test F1 to 83.1 (5.1 point absolute improvement).
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              The Social Amplification of Risk: A Conceptual Framework

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                Author and article information

                Contributors
                Journal
                Front Public Health
                Front Public Health
                Front. Public Health
                Frontiers in Public Health
                Frontiers Media S.A.
                2296-2565
                17 November 2022
                2022
                17 November 2022
                : 10
                : 978970
                Affiliations
                School of Management, Harbin Institute of Technology , Harbin, China
                Author notes

                Edited by: Raphael Cuomo, University of California, San Diego, United States

                Reviewed by: Junxiang Chen, University of Pittsburgh, United States; Dandan Wang, Wuhan University, China

                *Correspondence: Guang Yu yug@ 123456hit.edu.cn

                This article was submitted to Digital Public Health, a section of the journal Frontiers in Public Health

                Article
                10.3389/fpubh.2022.978970
                9714350
                8e9329f7-9d96-4be2-9331-1e5107ea93aa
                Copyright © 2022 Yu, Yu, Li and Li.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 June 2022
                : 17 October 2022
                Page count
                Figures: 7, Tables: 3, Equations: 0, References: 31, Pages: 13, Words: 8324
                Funding
                Funded by: National Natural Science Foundation of China, doi 10.13039/501100001809;
                Categories
                Public Health
                Original Research

                covid-19,social media,sentiment classification,communication effect,24-h livestream

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