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1.
《Information processing & management》2023,60(3):103299
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
2.
《Information processing & management》2022,59(4):102959
False news that spreads on social media has proliferated over the past years and has led to multi-aspect threats in the real world. While there are studies of false news on specific domains (like politics or health care), little work is found comparing false news across domains. In this article, we investigate false news across nine domains on Weibo, the largest Twitter-like social media platform in China, from 2009 to 2019. The newly collected data comprise 44,728 posts in the nine domains, published by 40,215 users, and reposted over 3.4 million times. Based on the distributions and spreads of the multi-domain dataset, we observe that false news in domains that are close to daily life like health and medicine generated more posts but diffused less effectively than those in other domains like politics, and that political false news had the most effective capacity for diffusion. The widely diffused false news posts on Weibo were associated strongly with certain types of users — by gender, age, etc. Further, these posts provoked strong emotions in the reposts and diffused further with the active engagement of false-news starters. Our findings have the potential to help design false news detection systems in suspicious news discovery, veracity prediction, and display and explanation. The comparison of the findings on Weibo with those of existing work demonstrates nuanced patterns, suggesting the need for more research on data from diverse platforms, countries, or languages to tackle the global issue of false news. The code and new anonymized dataset are available at https://github.com/ICTMCG/Characterizing-Weibo-Multi-Domain-False-News. 相似文献
3.
《Information processing & management》2022,59(5):102997
Social media like Weibo has become an important platform for people to ask for help during COVID-19 pandemic. Using a complete dataset of help-seeking posts on Weibo during the COVID-19 outbreak in China (N = 3,705,188), this study mapped their characteristics and analyzed their relationship with the epidemic development at the aggregate level, and examined the influential factors to determine whether and the extent the help-seeking crying could be heard at the individual level using computational methods for the first time. It finds that the number of help-seeking posts on Weibo has a Granger causality relationship with the number of confirmed COVID-19 cases with a time lag of eight days. This study then proposes a 3C framework to examine the direct influence of content, context, and connection on the responses (measured by retweets and comments) and assistance that help-seekers might receive as well as their indirect effects on assistance through the mediation of both retweets and comments. The differential influences of content (theme and negative sentiment), context (Super topic community, spatial location of posting, and the period of sending time), and connection (the number of followers, whether mentioning others, and verified status of authors and sharers) have been reported and discussed. 相似文献
4.
When public events occur, users often generate a huge number of microblog entries and their online interactions with one another. Forwarding and commenting on posts contribute to the huge networks of topic and sentiment communication. This study constructs the topic and sentiment propagation maps of microblogging in the context of public events to visually explore the patterns of topic and sentiment propagation among stakeholders across different phases. To quantify the influence of topic and sentiment propagation, four indicators of “topic out-degree,” “topic variation degree,” “sentiment out-degree,” and “sentiment deviation degree” are proposed. We chose the child abuse case in the Beijing Red-Yellow-Blue (RYB) Kindergarten for our study. The positions of various stakeholders in the propagation paths and the relationship among stakeholders were revealed. Results indicate that the government and mainstream media have the greatest influence in terms of topic and sentiment propagation. Moreover, topic propagation was the most influential in the recession phase and the same can be said with sentiment propagation in the spreading phase. The findings can help the emergency management departments gain a better understanding of the propagation patterns of topics and emotions and the role of stakeholders in such phenomena to improve their emergency response ability. 相似文献
5.
【目的/意义】微博是公共图书馆进行社会推广、业界交流、用户交互的重要渠道,从社会网络视角分析公共图书馆微博意见领袖的社会网络结构特点及影响力,可为公共图书馆优化微博营销策略、提高自身影响力提供参考。【方法/过程】选取50位公共图书馆微博意见领袖,首先运用社会网络分析方法揭示其社会网络结构特点;其次利用关注量、发文量、粉丝量、转评赞数量分析其活跃情况及影响力。【结果/结论】公共图书馆微博意见领袖地区分布不均衡,联系较紧密,但集中程度较弱;小团体在活跃度、影响力等方面呈现相似性;多数图书馆处于低活跃度、低影响力区间;粉丝量和转评赞数量随着活跃度的提升表现出“低值时平稳波动,高值时迅速增长”的现象。【创新/局限】通过社会网络分析方法在一定程度上掌握了我国公共图书馆微博意见领袖社会结构及影响力。仅从关注量、发文量等客观数据角度分析公共图书馆微博影响力,未来应结合文本分析等方法提高影响力分析的深度。 相似文献
6.
【目的/意义】以近两年（2018-2019）国内有代表性的四件负面公共安全突发事件为例,对其微博评论进行
聚类,并找出影响微博用户消极情感倾向的因素,为政府进行舆情应对处理提供建议。【方法/过程】结合社会网络
分析法与LDA主题模型对评论文本进行关键要素提取,得出评论归因维度,进而通过情感分析软件对各维度进行
情感倾向度分析。【结果/结论】研究结果表明：微博用户主要从事件主体、事件分析、事件处置、社会关系、新闻媒
体、同理心、个人经验七个方面对公共安全突发事件进行评论,其中,事件分析、事件处置、事件主体、社会关系是微
博用户消极情感倾向的主要影响因素,据此本文提出了相应的舆情疏导建议。【创新/局限】本文基于归因理论,创
新性的提出了影响微博用户情感倾向度的归因维度体系,但舆情事件集中数量有限且未进行更细粒度的情感分类
分析。 相似文献
7.
《Information processing & management》2022,59(4):102990
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
8.
【目的/意义】通过研究微博社区网民的情感交互与舆情观点,有助于在复杂的网络中掌握网民情绪演化从而良性引导网络舆情态势。【方法/过程】基于传播动力学、社会安全阀等理论,结合微博社区中的实际案例,定义事件利益主体并抽象出事件演化的全生命周期,同时,构建SIR演化博弈模型刻画网民情绪的动态演化规律及主体决策博弈演化过程,并通过仿真模拟分析得到系统演化至稳定状态的均衡条件。【结果/结论】结果表明:微博社区中意见领袖与官方媒体感知收益与风险的敏感度对决策行为产生显著影响;官方媒体及时设置有效议程构建安全阀能够防止网民情绪恶化;意见领袖与官方媒体的协同引导能够最大效度地帮助政府管控网络舆情。 相似文献
9.
The increased availability of social media big data has created a unique challenge for marketing decision-makers; turning this data into useful information. One of the significant areas of opportunity in digital marketing is influencer marketing, but identifying these influencers from big data sets is a continual challenge. This research illustrates how one type of influencer, the market maven, can be identified using big data. Using a mixed-method combination of both self-report survey data and publicly accessible big data, we gathered 556,150 tweets from 370 active Twitter users. We then proposed and tested a range of social-media-based metrics to identify market mavens. Findings show that market mavens (when compared to non-mavens) have more followers, post more often, have less readable posts, use more uppercase letters, use less distinct words, and use hashtags more often. These metrics are openly available from public Twitter accounts and could integrate into a broad-scale decision support system for marketing and information systems managers. These findings have the potential to improve influencer identification effectiveness and efficiency, and thus improve influencer marketing. 相似文献
10.
在社会化媒体时代,如何在创新社区的海量数据环境中识别出领先用户,是企业从创新社区中获取价值的关键问题。本文从语言风格的视角出发,首先通过内容分析法探索了创新社区中领先用户表达的典型语言风格特征,即成就需求、未来导向、积极情绪和集体主义。其次,收集了355名创新社区用户所发表的47310篇帖子,利用自动文本分析方法对其中包含的积极情绪、集体主义和未来导向语言风格进行了测量,并验证了这四种语言风格与用户领先性的关系。研究结果表明,创新社区用户生成内容中所表现的语言风格起到了“信号”的作用：除了集体主义之外,成就需求、未来导向和积极情绪的语言风格都与用户领先性有显著的正向关系,可以作为识别领先用户的有效指标。最后,讨论了基于语言风格的领先用户识别机制的理论意义和实践价值。 相似文献
11.
Research typically focuses on one medium. But in today's digital media environment, people use and are influenced by their experience with multiple systems. Building on media ecology research, we introduce the notion of integrated media effects. We draw on resource dependence and homophily theories to analyze the mechanisms that connect media systems. To test the integrated media effects, we examine the relationships between news media visibility and social media visibility and hyperlinking patterns among 410 nongovernmental organization (NGO) websites in China. NGOs with greater news media visibility and more social media followers receive significantly more hyperlinks. Further, NGOs with a similar number of social media followers prefer to hyperlink to each other. The results suggest that both news media and social media systems are related to the configuration of hyperlink networks, providing support for the integrated media effects described. Implications for the study of hyperlink networks, online behaviors of organizations, and public relations are drawn from the results. 相似文献
12.
13.
《Information processing & management》2020,57(6):102354
Nowadays, it is a common practice for healthcare professionals to spread medical knowledge by posting health articles on social media. However, promoting users’ intention to share such articles is challenging because the extent of sharing intention varies in their eHealth literacy (high or low) and the content valence of the article that they are exposed to (positive or negative). This study investigates boundary conditions under which eHealth literacy and content valence help to increase users’ intention to share by introducing a moderating role of confirmation bias—a tendency to prefer information that conforms to their initial beliefs. A 2 (eHealth literacy: high vs. low) × 2 (content valence: positive vs. negative) between-subjects experiment was conducted in a sample of 80 participants. Levels of confirmation bias ranging from extreme negative bias to extreme positive bias among the participants were assessed during the experiment. Results suggested that: (1) users with a high level of eHealth literacy were more likely to share positive health articles when they had extreme confirmation bias; (2) users with a high level of eHealth literacy were more likely to share negative health articles when they had moderate confirmation bias or no confirmation bias; (3) users with a low level of eHealth literacy were more likely to share health articles regardless of positive or negative content valence when they had moderate positive confirmation bias. This study sheds new light on the role of confirmation bias in users’ health information sharing. Also, it offers implications for health information providers who want to increase the visibility of their online health articles: they need to consider readers’ eHealth literacy and confirmation bias when deciding the content valence of the articles. 相似文献
14.
【目的/意义】研究社交网络中影响辟谣信息传播效果的因素,丰富了辟谣有效性的理论,为相关部门制定
提升辟谣信息传播效果策略提供依据。【方法/过程】基于流行三要素理论总结辟谣信息传播效果的影响因素,通过
情感分析、社交网络分析和多元回归分析验证影响辟谣信息传播效果的因素。【结果/结论】粉丝数、情感倾向、“真
相陈述”和“直接反驳+真相陈述”的辟谣方式、原创性、“文字+图片”、休闲时间、网络规模、网络密度和平均路径长
度显著影响辟谣信息的评论数和转发数;辟谣信息中含有@显著正向影响转发数,含有链接显著正向影响评论数。
【创新/局限】基于流行三要素理论对社交网络中辟谣信息传播效果的影响因素进行提炼,并考虑群体因素,利用社
交网络数据进行实证研究,为后续的相关研究提供参考依据,但是本文未考虑到平台因素和粉丝个人属性因素等,
后续研究中需要进一步探讨。 相似文献
15.
The dissemination of misinformation in health emergencies poses serious threats to public health and increases health anxiety. To understand the underlying mechanism of the dissemination of misinformation regarding health emergencies, this study creatively draws on social support theory and text mining. It also explores the roles of different types of misinformation, including health advice and caution misinformation and health help-seeking misinformation, and emotional support in affecting individuals’ misinformation dissemination behavior on social media and whether such relationships are contingent on misinformation ambiguity and richness. The theoretical model is tested using 12,101 textual data about COVID-19 collected from Sina Weibo, a leading social media platform in China. The empirical results show that health caution and advice, help seeking misinformation, and emotional support significantly increase the dissemination of misinformation. Furthermore, when the level of ambiguity and richness regarding misinformation is high, the effect of health caution and advice misinformation is strengthened, whereas the effect of health help-seeking misinformation and emotional support is weakened, indicating both dark and bright misinformation ambiguity and richness. This study contributes to the literature on misinformation dissemination behavior on social media during health emergencies and social support theory and provides implications for practice. 相似文献
16.
《International Journal of Information Management》2016,36(3):360-373
As social network services become more pervasive, social media advertising emerges as an attractive vehicle for augmenting advertising effectiveness. To leverage this new means of marketing, one must understand what engages SNS users in a favorable online behavior (i.e., overtly indicating personal interest in, or support for, the exposed message by clicking the Like or Share button in Facebook), thereby resulting in an effective advertising campaign. This research conceptualizes SNS ad effectiveness as a concept encompassing emotional appeal, informativeness and creativity that all have a potential to contribute to a positive online behavior. It empirically investigates the antecedents of positive user behavior for a SNS ad based on the theory of reasoned action, the social influence theory, and a persuasion theory. It proposes and tests a conceptual model of the formation of online user’s behavioral responses with regards to SNS advertising. The results of our empirical tests of the model reveal that informativeness and advertising creativity were key drivers of favorable behavioral responses to an SNS ad and that intention to engage in favorable user responses was positively associated with purchase intention. Based on these findings, the paper suggests further research directions and offers implications for harnessing the full potential of the new SNS advertising platform. 相似文献
17.
《Information processing & management》2022,59(5):103035
The loss of followers poses a severe threat to the development of microblogging platforms and bloggers. However, the reasons behind users’ unfollowing behavior remain unclear. Drawing on the person-environment fit framework, we examined how different types of person-environment misfits affect users’ unfollowing intention and the relationship between these misfits. We collected the data to test the research model from 305 Weibo users via an online survey. The results suggest that from the perspective of complementary misfit, information overload increases social media fatigue, and information irrelevance increases followers’ expectation disconfirmation. From the perspective of supplementary misfit, perceived value dissimilarity positively affects followers’ fatigue and disconfirmation. These negative psychological states consequently lead to followers’ unfollowing intention. Furthermore, our results revealed the positive effects of perceived value dissimilarity on information overload and information irrelevance. We also discuss the theoretical contributions and practical implications of this study. 相似文献
18.
Rapid communication during extreme events is one of the critical aspects of successful disaster management strategies. Due to their ubiquitous nature, social media platforms are expected to offer a unique opportunity for crisis communication. In this study, about 52.5 million tweets related to hurricane Sandy posted by 13.75 million users are analyzed to assess the effectiveness of social media communication during disasters and identify the contributing factors leading to effective crisis communication strategies. Efficiency of a social media user is defined as the ratio of attention gained over the number of tweets posted. A model is developed to identify more efficient users based on several relevant features. Results indicate that during a disaster event, only few social media users become highly efficient in gaining attention. In addition, efficiency does not depend on the frequency of tweeting activity only; instead it depends on the number of followers and friends, user category, bot score (controlled by a human or a machine), and activity patterns (predictability of activity frequency). Since the proposed efficiency metric is easy to evaluate, it can potentially detect effective social media users in real time to communicate information and awareness to vulnerable communities during a disaster. 相似文献
19.
《Information processing & management》2022,59(2):102846
With the advent of the era of “we media,” many people's opinions have become easily accessible. Public health emergencies have always been an important aspect of public opinion exchange and emotional communication. In view of this sudden group panic, public opinion cannot be effectively monitored, controlled or guided. This makes it easy to amplify the beliefs and irrationality of social emotions, that threaten social security and stability. Considering the important role of opinion leaders in micro-blogs and users’ interest in micro-blog information, a SIR model of public opinion propagation is constructed based on the novel coronavirus pneumonia model and micro-blog's public health emergencies information. The parameters of the model are calculated by combining the actual crawl data from the novel coronavirus pneumonia epidemic period, and the trends in the evolution of public opinion are simulated by MATLAB. The simulation results are consistent with the actual development of public opinion dissemination, which shows the effectiveness of the model. These research findings can help the government understand the principles that guide the propagation of public opinion and advise an appropriate time to control and correctly guide public opinion. 相似文献
20.
The rising popularity of social media posts, most notably Twitter posts, as a data source for social science research poses significant problems with regard to access to representative, high-quality data for analysis. Cheap, publicly available data such as that obtained from Twitter's public application programming interfaces is often of low quality, while high-quality data is expensive both financially and computationally. Moreover, data is often available only in real-time, making post-hoc analysis difficult or impossible. We propose and test a methodology for inexpensively creating an archive of Twitter data through population sampling, yielding a database that is highly representative of the targeted user population (in this test case, the entire population of Japanese-language Twitter users). Comparing the tweet volume, keywords, and topics found in our sample data set with the ground truth of Twitter's full data feed confirmed a very high degree of representativeness in the sample. We conclude that this approach yields a data set that is suitable for a wide range of post-hoc analyses, while remaining cost effective and accessible to a wide range of researchers. 相似文献