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1.
With the onset of COVID-19, the pandemic has aroused huge discussions on social media like Twitter, followed by many social media analyses concerning it. Despite such an abundance of studies, however, little work has been done on reactions from the public and officials on social networks and their associations, especially during the early outbreak stage. In this paper, a total of 9,259,861 COVID-19-related English tweets published from 31 December 2019 to 11 March 2020 are accumulated for exploring the participatory dynamics of public attention and news coverage during the early stage of the pandemic. An easy numeric data augmentation (ENDA) technique is proposed for generating new samples while preserving label validity. It attains superior performance on text classification tasks with deep models (BERT) than an easier data augmentation method. To demonstrate the efficacy of ENDA further, experiments and ablation studies have also been implemented on other benchmark datasets. The classification results of COVID-19 tweets show tweets peaks trigged by momentous events and a strong positive correlation between the daily number of personal narratives and news reports. We argue that there were three periods divided by the turning points on January 20 and February 23 and the low level of news coverage suggests the missed windows for government response in early January and February. Our study not only contributes to a deeper understanding of the dynamic patterns and relationships of public attention and news coverage on social media during the pandemic but also sheds light on early emergency management and government response on social media during global health crises.  相似文献   

2.
Abstract

The research on online news comments has been dominated by a normative approach and has centered on media engagement. Normativity and media dominance have also featured big in the theoretical discussions on the public sphere. This article presents a case study of online news comments, combining a novel methodological testing of social network hypotheses to examine user–user interactions in online comments with a conceptual discussion of the potential connections between social network research and theories of the public. The social network analysis in this study indicated that users (online commentators) do not constitute highly dense networks, although their relations can be studied as social networks. However, this analysis can only explore limited features of this online phenomenon and requires complementary methods. From a conceptual perspective, this article confirms the role of shared issue for a potential public and also emphasizes the importance of context, actors, and meanings for understanding the public.  相似文献   

3.
[目的/意义]新型冠状病毒肺炎疫情(简称新冠肺炎疫情)的全球蔓延引发了各领域学者对于突发公共卫生事件科学应对的思考。文章以新冠肺炎疫情为例,以微博为研究对象,旨在探讨突发公共卫生事件中公众的信息需求对于危机治理的影响机制。[方法/过程]首先,对新冠肺炎疫情及微博舆情做出阶段划分,进而利用质性分析结合层次聚类法从微博文本数据中抽取公众信息需求并跟踪其演变,最终结合相关理论探索性地建立了突发公共卫生事件公众信息需求模型。[结果/结论]突发公共卫生事件中公众的信息需求主要围绕风险认知、行为规范、情感、行为四个方面,通过社交媒体可以准确追踪公众信息需求并向公众提供所需信息,信息需求的满足最终促使公众自发参与危机治理。  相似文献   

4.
The implementation of digital contact tracing applications around the world to help reduce the spread of the COVID-19 pandemic represents one of the most ambitious uses of massive-scale citizen data ever attempted. There is major divergence among nations, however, between a “privacy-first” approach which protects citizens’ data at the cost of extremely limited access for public health authorities and researchers, and a “data-first” approach which stores large amounts of data which, while of immeasurable value to epidemiologists and other researchers, may significantly intrude upon citizens’ privacy. The lack of a consensus on privacy protection in the contact tracing process creates risks of non-compliance or deliberate obfuscation from citizens who fear revealing private aspects of their lives – a factor greatly exacerbated by recent major scandals over online privacy and the illicit use of citizens’ digital information, which have heightened public consciousness of these issues and created significant new challenges for any collection of large-scale public data. While digital contact tracing for COVID-19 remains in its infancy, the lack of consensus around best practices for its implementation and for reassuring citizens of the protection of their privacy may already have impeded its capacity to contribute to the pandemic response.  相似文献   

5.
As social distancing and lockdown orders grew more pervasive, individuals increasingly turned to social media for support, entertainment, and connection to others. We posit that global health emergencies - specifically, the COVID-19 pandemic - change how and what individuals self-disclose on social media. We argue that IS research needs to consider how privacy (self-focused) and social (other-focused) calculus have moved some issues outside in (caused by a shift in what is considered socially appropriate) and others inside out (caused by a shift in what information should be shared for the public good). We identify a series of directions for future research that hold potential for furthering our understanding of online self-disclosure and its factors during health emergencies.  相似文献   

6.
Documenting the emergent social representations of COVID-19 in public communication is necessary for critically reflecting on pandemic responses and providing guidance for global pandemic recovery policies and practices. This study documents the dynamics of changing social representations of the COVID-19 pandemic on one of the largest Chinese social media, Weibo, from December 2019 to April 2020. We draw on the social representation theory (SRT) and conceptualize topics and topic networks as a form of social representation. We analyzed a dataset of 40 million COVID-19 related posts from 9.7 million users (including the general public, opinion leaders, and organizations) using machine learning methods. We identified 12 topics and found an expansion in social representations of COVID-19 from a clinical and epidemiological perspective to a broader perspective that integrated personal illness experiences with economic and sociopolitical discourses. Discussions about COVID-19 science did not take a prominent position in the representations, suggesting a lack of effective science and risk communication. Further, we found the strongest association of social representations existed between the public and opinion leaders and the organizations’ representations did not align much with the other two groups, suggesting a lack of organizations’ influence in public representations of COVID-19 on social media in China.  相似文献   

7.
面对新形势下党治国理政的新场景和种种挑战,提升网络新闻舆论阵地引导力是信息化时代促进国家治理能力现代化的重要方面,在当前社会多元化趋势下要充分运用党的网络新闻舆论阵地有效地引领思想舆论和凝聚社会共识。网络新闻舆论阵地要通过内容呈现、方法适应、共同治理三个层面的优化和有机统一共同发挥党的思想政治教育优势、释放网络引领正能量,使之成为“丰富人民精神世界,增强人民精神力量”的前沿高地。  相似文献   

8.
The wide spread of fake news and its negative impacts on society has attracted a lot of attention to fake news detection. In existing fake news detection methods, particular attention has been paid to the credibility of the users sharing the news on social media, and the news sources based on their level of participation in fake news dissemination. However, these methods have ignored the important role of news topical perspectives (like political viewpoint) in users'/sources' decisions to share/publish the news. These decisions are associated with the viewpoints shared by the echo-chamber that the users belong to, i.e., users' Socio-Cognitive (SC) biases, and the news sources' partisan bias. Therefore, the credibility of users and news sources are varied in different topics according to the mentioned biases; which are completely ignored in current fake news detection studies. In this paper, we propose a Multi-View Co-Attention Network (MVCAN) that jointly models the latent topic-specific credibility of users and news sources for fake news detection. The key idea is to represent news articles, users, and news sources in a way that the topical viewpoints of news articles, SC biases of users which determines the users' viewpoints in sharing news, and the partisan bias of news sources are encoded as vectors. Then a novel variant of the Multi-Head Co-Attention (MHCA) mechanism is proposed to encode the joint interaction from different views, including news-source and news-user to implicitly model the credibility of users and the news sources based on their interaction in real and fake news spreading on the news topic. We conduct extensive experiments on two public datasets. The results show that MVCAN significantly outperforms other state-of-the-art methods and outperforms the best baselines by 3% on average in terms of F1 and Accuracy.  相似文献   

9.
During the COVID-19 pandemic, a plethora of online sources for information and news dissemination have emerged. Extant research suggests that very quickly, individuals become disinterested and begin avoiding the information. In this study, we investigate how an individual's fear and situational motivation impact Online Information Avoidance. Using the self-determination theory and information avoidance theories, we argue that fear and external regulation are associated with increased Online Information Avoidance. We also argue that intrinsic motivation and identified regulation are associated with a decrease in Online Information Avoidance. Our findings suggest that fear, intrinsic motivation, and external regulation drive Online Information Avoidance, where intrinsic motivation is the most significant driver. We also found that identified regulation is a crucial inhibitor of Online Information Avoidance. While focusing on COVID-19, our study contributes to the broader information systems research literature and specifically to the information avoidance literature during a pandemic or a prolonged crisis. Our study's findings will be useful for governments, health organizations, and communities that utilize online platforms, forums, and related outlets to reach larger audiences for disseminating pertinent information and recommendations during a crisis.  相似文献   

10.
《Research Policy》2022,51(1):104393
In this paper we draw a parallel between the insights developed within the framework of the current COVID-19 health crisis and the views and insights developed with respect to the long term environmental crisis, the implications for science, technology and innovation (STI) policy, Christopher Freeman analyzed already in the early 90′s. With at the time of writing, the COVID-19 pandemic entering in many countries a third wave with a very differentiated implementation path of vaccination across rich and poor countries, drawing such a parallel remains of course a relatively speculative exercise. Nevertheless, based on the available evidence of the first wave of the pandemic, we feel confident that some lessons from the current health crisis and its parallels with the long-term environmental crisis can be drawn. The COVID-19 pandemic has also been described as a “syndemic”: a term popular in medical anthropology which marries the concept of ‘synergy’ with ‘epidemic’ and provides conceptually an interesting background for these posthumous Freeman reflections on crises. The COVID-19 crisis affects citizens in very different and disproportionate ways. It results not only in rising structural inequalities among social groups and classes, but also among generations. In the paper, we focus on the growing inequality within two particular groups: youngsters and the impact of COVID-19 on learning and the organization of education; and as mirror picture, the elderly many of whom witnessed despite strict confinement in long-term care facilities, high mortality following the COVID-19 outbreak. From a Freeman perspective, these inequality consequences of the current COVID-19 health crisis call for new social STI policies: for a new “corona version” of inclusion versus exclusion.  相似文献   

11.
In the period of Corona Virus Disease 2019 (COVID-19), millions of people participate in the discussion of COVID-19 on the Internet, which can easily trigger public opinion and threaten social stability. This paper creatively proposes a multi-stage risk grading model of Internet public opinion for public health emergencies. On the basis of general public opinion risk grading analysis, the model continuously pays attention to the risk level of Internet public opinion based on the time scale of regular or major information updates. This model combines Analytic Hierarchy Process Sort II (AHPSort II) and Swing Weighting (SW) methods and proposes a new Multi-Criteria Decision Making (MCDM) method – AHPSort II-SW. Intuitionistic fuzzy number and linguistic fuzzy number are introduced into the model to evaluate the criteria that cannot be quantified. The multi-stage model is tested using more than 2,000 textual data about COVID-19 collected from Microblog, a leading social media platform in China. Seven public opinion risk assessments were conducted from January 23 to April 8, 2020. The empirical results show that in the early COVID-19 outbreak, the risk of public opinion is more serious on macroscopic view. In details, the risk of public opinion decreases slowly with time, but the emergence of important events may still increase the risk of public opinion. The analysis results are in line with the actual situation and verify the effectiveness of the method. Comparative analysis indicates the improved method is proved to be superior and effective, sensitivity analysis confirms its stability. Finally, management suggestions was provided, this study contributes to the literature on public opinion risk assessment and provides implications for practice.  相似文献   

12.
As COVID-19 swept over the world, people discussed facts, expressed opinions, and shared sentiments about the pandemic on social media. Since policies such as travel restriction and lockdown in reaction to COVID-19 were made at different levels of the society (e.g., schools and employers) and the government, we build a large geo-tagged Twitter dataset titled UsaGeoCov19 and perform an exploratory analysis by geographic location. Specifically, we collect 650,563 unique geo-tagged tweets across the United States covering the date range from January 25 to May 10, 2020. Tweet locations enable us to conduct region-specific studies such as tweeting volumes and sentiment, sometimes in response to local regulations and reported COVID-19 cases. During this period, many people started working from home. The gap between workdays and weekends in hourly tweet volumes inspire us to propose algorithms to estimate work engagement during the COVID-19 crisis. This paper also summarizes themes and topics of tweets in our dataset using both social media exclusive tools (i.e., #hashtags, @mentions) and the latent Dirichlet allocation model. We welcome requests for data sharing and conversations for more insights.UsaGeoCov19 link: http://yunhefeng.me/geo-tagged_twitter_datasets/.  相似文献   

13.
面向社科领域的网络新闻分析与监测   总被引:1,自引:0,他引:1  
通过自然语言处理技术和数理统计方法的运用,网络新闻在经济金融、公共卫生、政治科学、科研管理、舆情监测与预警等社会科学领域具有很大的利用价值。对新闻分析与监测在各个社会科学领域的应用现状进行分析和综述,包括新闻来源、关键技术、领域特点、实施方法和典型系统,总结得出当前研究的特点及发展趋势。  相似文献   

14.
Mobile health (mHealth) applications have become an important tool to support public health, especially in times of increased health awareness in the midst of the COVID-19 pandemic. However, there is still uncertainty about what factors determine successful mHealth services from the users’ perspective. Based on the results of a systematic literature review, a qualitative content analysis of available apps and semi-structured user and expert interviews, we derive a structural model with antecedents on user attitudes towards mHealth and user satisfaction with the mHealth application. These variables determine users’ intention to continue using the application and their intention to recommend it to others. For verification, we tested the model with a sample of 249 German mHealth users from the “MyFitnessPal” community using structural equation modelling and found that all derived path relations have significant coefficients.  相似文献   

15.
As a global health crisis, the COVID-19 pandemic has also made heavy mental and emotional tolls become shared experiences of global communities, especially among females who were affected more by the pandemic than males for anxiety and depression. By connecting multiple facets of empathy as key mechanisms of information processing with the communication theory of resilience, the present study examines human-AI interactions during the COVID-19 pandemic in order to understand digitally mediated empathy and how the intertwining of empathic and communicative processes of resilience works as coping strategies for COVID-19 disruption. Mixed methods were adopted to explore the using experiences and effects of Replika, a chatbot companion powered by AI, with ethnographic research, in-depth interviews, and grounded theory-based analysis. Findings of this research extend empathy theories from interpersonal communication to human-AI interactions and show five types of digitally mediated empathy among Chinese female Replika users with varying degrees of cognitive empathy, affective empathy, and empathic response involved in the information processing processes, i.e., companion buddy, responsive diary, emotion-handling program, electronic pet, and tool for venting. When processing information obtained from AI and collaborative interactions with the AI chatbot, multiple facets of mediated empathy become unexpected pathways to resilience and enhance users’ well-being. This study fills the research gap by exploring empathy and resilience processes in human-AI interactions. Practical implications, especially for increasing individuals’ psychological resilience as an important component of global recovery from the pandemic, suggestions for future chatbot design, and future research directions are also discussed.  相似文献   

16.
刘继  武梦娇 《情报杂志》2021,(3):187-192,103
[目的/意义]重大突发事件对提高国家社会治理能力提出了新的要求,提升网络舆情态势评估能力成为创新社会治理的重要内容。[方法/过程]该文从网络舆情事件特征、关注度、传播扩散度及网民观点倾向等方面构建网络舆情态势评估指标,利用贝叶斯网络构建网络舆情态势评估模型,以“新冠肺炎疫情”事件为例,对网络舆情态势进行评估分析。[结果/结论]通过对网络舆情事件的测试,本文提出的方法具有较好的舆情态势评估效能,对“新冠肺炎疫情”相关网络舆情治理提出了建议。  相似文献   

17.
Understanding the effects of gender-specific emotional responses on information sharing behaviors are of great importance for swift, clear, and accurate public health crisis communication, but remains underexplored. This study fills this gap by investigating gender-specific anxiety- and anger-related emotional responses and their effects on the virality of crisis information by creatively drawing on social role theory, integrated crisis communication modeling, and text mining. The theoretical model is tested using two datasets (Changsheng vaccine crisis with 2,423,074 textual data and COVID-19 pandemic with 893,930 textual data) collected from Weibo, a leading social media platform in China. Females express significantly high anxiety and anger levels (p value<0.001) during the Changsheng fake vaccine crisis, while express significantly higher levels of anxiety during COVID-19 than males (p value<0.001), but not anger (p value=0.13). Regression analysis suggests that the virality of crisis information is significantly strengthened when the level of anger in posts of males is high or the level of anxiety in posts of females is high for both crises. However, such gender-specific virality differences of anger/anxiety expressions are violated once females have large numbers of followers (influencers). Furthermore, the gender-specific emotional effects on crisis information are more significantly enhanced for male influencers than female influencers. This study contributes to the literature on gender-specific emotional characteristics of crisis communication on social media and provides implications for practice.  相似文献   

18.
During the coronavirus pandemic, policy makers need to interpret available public health data to make decisions affecting public health. However, the United States’ coronavirus response faced data gaps, inadequate and inconsistent definitions of data across different governmental jurisdictions, ambiguous timing in reporting, problems in accessing data, and changing interpretations from scientific institutions. These present numerous problems for the decision makers relying on this information. This paper documents some of the data pitfalls in coronavirus public health data reporting, as identified by the authors in the course of supporting data management for New England’s coronavirus response. We provide recommendations for individuals to collect data more effectively during emergency situations such as a COVID-19 surge, as well as recommendations for institutions to provide more meaningful data for various users to access. Through this, we hope to motivate action to avoid data pitfalls during public health responses in the future.  相似文献   

19.
王晨 《情报探索》2021,(3):61-68
[目的/意义]研究微信公众号在反电信网络诈骗犯罪宣传中的作用和效果,对普及公众防骗意识、提高宣传效率,遏制电信网络诈骗犯罪发生具有重要意义。[方法/过程]根据微信使用群体广、消息易扩散、传播渠道多等特点,在“电诈可防”理念背景下,采用改进的SEIR模型分析甘肃省兰州市“反电信网络诈骗中心”微信公众号对涉疫情电信网络诈骗犯罪宣传效果。[结果/结论]本地政务微信的关注群体仍以本地微信用户为主,公众号新增“关注用户”和新增“取关用户”均在文章发布时段后达到峰值,且呈现正相关,较从文章读者中产生“关注用户”相比,直接吸引公众号本体“关注用户”方式将更为直接和有效。  相似文献   

20.
在国际科技竞争日益激化、我国科技实力迅速腾飞的当下,国家科学形象日益成为国家形象立体化过程中不可忽视的重要组成部分。通过对国际社交媒体推特平台上有关中国科学相关议题讨论的分析发现,西方公众目前对于中国科学类相关议题的关注度并不高,讨论由少量的主要科学事件主导,明显受到了西方主流新闻媒体与政治话语力量的引导与掌控,且认知偏向于负面。这种负面形象的“他塑”建构在一定程度上被卷入政治话语与国际关系话语体系中,表征为对中国负面科技新闻的报道及阴谋论的关注。而正面积极的科学形象则更多表征为“去政治化”语境下,对中国突破性科学成果与获得国际科学奖项科学家的赞赏,以及对于中国科幻的格外关注。对此,提升中国国际科学形象需要在重视社交媒体平台这一舆论场域的基础上,结合研究结果,制定具有针对性的对外科技传播策略。  相似文献   

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