Understanding the dynamics and duration of trending topics on digital platforms has been deemed a crucial issue of research in computer-mediated communication. Employing event history analysis (EHA), this study attempts to examine the antecedents of the lifespan and evolution of trending topics on Sina Weibo, one of the most prevalent social media platforms in China. Based on a collection of 2,386 Sina Weibo trending topics that emerged between January 1 and January 31, 2022, the study explores how factors of trending topics, especially their semantic and textual features, significantly influence topic persistence. Our findings indicate that the median survival time of Weibo trending topic was 6.28 hours, with an average of 8.29 hours. In addition, exogenous non-viral topics, driven by external events or media coverage, tend to remain on the trending list longer than other topics. Furthermore, political topics tend to have a relatively longer period of survival duration when compared to social events, life records and moods, and fashion and entertainment topics. Lastly, actionable and opinion-oriented topics tend to have shorter longevity compared to informational and emotional topics. By quantifying the factors that affect trending topic duration, the study offers a novel theoretical perspective on the role of political drivers and external influences in shaping collective and connective digital discourses. The findings contribute to the broader field of digital platform communication, particularly in public opinion management and content governance on social media.

The application of generative artificial intelligence (GenAI) technologies in the field of propaganda influences information creation, dissemination, and reception, and introduces new ethical challenges. This paper revisits the philosophical discourses of Jacques Ellul on technology and propaganda, placing them within the context of the rise of today’s generative AI technologies. Ellul identified the First Industrial Revolution as the initial juncture in the history of human technology that formed technique as a social phenomenon, which subsequently shaped the nature of propaganda as a technique. Subsequent developments in computer technology in the latter half of the 20th century enabled the formation of a technological system. This raises the question: Could generative AI represent another pivotal moment in the evolution of the technological system, and what are the ethical implications of propaganda technology in this context? This article seeks to illuminate current discussions on GenAI technology and propaganda ethics with Ellul’s insightful theoretical insights. In terms of research methodology, this study relies on textual interpretation and classical hermeneutics, including three processes: syntactic text interpretation, historical background, and situational application. Ellul’s research delves into the intrinsic links and inherent ethical dimensions between propaganda and technology, examining their comprehensive and enduring impacts. This normative perspective is crucial for a deep understanding of contemporary propaganda within the framework of emerging technologies, helping us to transcend the escalating spiral of propaganda technology and counter-propaganda techniques. By incorporating propaganda facilitated by generative AI technologies into the overall development logic of the technological society, this approach explores its ethical implications from a more macroscopic and holistic perspective.

Background The emergence of the COVID-19 pandemic towards the end of 2019 triggered a relentless spread of online misinformation, which significantly impacted societal stability, public perception, and the effectiveness of measures to prevent and control the epidemic. Understanding the complex dynamics and characteristics that determine the duration of rumors is crucial for their effective management. In response to this urgent requirement, our study takes survival analysis method to analyze COVID-19 rumors comprehensively and rigorously. Our primary aim is to clarify the distribution patterns and key determinants of their persistence. Through this exploration, we aim to contribute to the development of robust rumor management strategies, thereby reducing the adverse effects of misinformation during the ongoing pandemic. Methods The dataset utilized in this research was sourced from Tencent's “Jiao Zhen” Verification Platform's “Real-Time Debunking of Novel Coronavirus Pneumonia” system. We gathered a total of 754 instances of rumors from January 18, 2020, to January 17, 2023. The duration of each rumor was ascertained using the Baidu search engine. To analyze these rumors, survival analysis techniques were applied. The study focused on examining various factors that might influence the rumors' longevity, including the theme of the content, emotional appeal, the credibility of the source, and the mode of presentation. Results Our study's results indicate that a rumor's lifecycle post-emergence typically progresses through three distinct phases: an initial rapid decline phase (0–25 days), followed by a stable phase (25–1000 days), and ultimately, an extinction phase (beyond 1000 days). It is observed that half of the rumors fade within the first 25 days, with an average duration of approximately 260.15 days. When compared to the baseline category of prevention and treatment rumors, the risk of dissipation is markedly higher in other categories: policy measures rumors are 3.58 times more likely to perish, virus information rumors have a 0.52 times higher risk, epidemic situation rumors are 4.86 times more likely to die out, and social current affairs rumors face a 2.02 times increased risk. Additionally, in comparison to wish rumors, bogie rumors and aggression rumors have 0.26 and 0.27 times higher risks of dying, respectively. In terms of presentation, graphical and video rumors share similar dissolution risks, whereas textual rumors tend to have a longer survival time. Interestingly, the credibility of the rumor's source does not significantly impact its longevity. Conclusion The survival time of rumors is strongly linked to their content theme and emotional appeal, whereas the credibility of the source and the format of presentation have a more auxiliary influence. This study recommends that government agencies should adopt specific strategies to counter rumors. Experts and scholars are encouraged to take an active role in spreading health knowledge. It's important for the public to proactively seek trustworthy sources for accurate information. Media platforms are advised to maintain journalistic integrity, verify the accuracy of information, and guide the public towards improved media literacy. These actions, collectively, can foster a collaborative alliance between the government and the media, effectively combating misinformation.

With the increasing use of social media, online self-organized relief has become a crucial aspect of crisis management during public health emergencies, leading to the emergence of online self-organizations. This study employed the BERT model to classify the replies of Weibo users and used K-means clustering to summarize the patterns of self-organized groups and communities. We then combined the findings from pattern discovery and documents from online relief networks to analyze the core components and mechanisms of online self-organizations. Our findings indicate the following: (1) The composition of online self-organized groups follows Pareto's law. (2) Online self-organized communities are mainly composed of sparse and small groups with loose connections, and bot accounts can automatically identify those in need and provide them with helpful information and resources. (3) The core components of the mechanism of online self-organized rescue groups include the initial gathering of groups, the formation of key groups, the generation of collective action, and the establishment of organizational norms. This study suggests that social media can establish an authentication mechanism for online self-organizations, and that authorities should encourage online interactive live streams about public health issues. However, it is important to note that self-organizations are not a panacea for all issues during public health emergencies.

Based on Network Agenda Setting Model, this study collected 42,516 media reports from Party Media, commercial media, and We Media of China during the COVID-19 pandemic. We trained LDA models for topic clustering through unsupervised machine learning. Questionnaires (N = 470) and social network analysis methods were then applied to examine the correlation between media network agendas and public network agendas in terms of explicit and implicit topics. The study found that the media reports could be classified into 14 topics by the LDA topic modeling, and the three types of media presented homogeneity in the topics of their reports, yet had their own characteristics; there was a significant correlation between the media network agenda and the public network agenda, and the We Media reports had the most prominent effect on the public network agenda; the correlation between the media agenda and the implicit public agenda was higher than that of the explicit public agenda. Overall, findings showed a significant correlation between network agendas among different media.

Based on event history analysis, this study examined the survival distribution of the duration of online public opinions related to major health emergencies and its influencing factors. We analyzed the data of such emergencies (N = 125) that took place in China during a period of 10 years (2012-2021). The results of the Kaplan-Meier method and Cox proportional hazards regression analysis showed that the average duration of online public opinions regarding health emergencies is 43 days, and the median is 19 days, which dispels the myth of the "Seven-day Law of Propagation." Furthermore, the duration of online public opinions can be divided into three stages: the rapid decline stage (0-50 days), the slowdown stage (51-200 days), and the disappearing stage (after 200 days). In addition, the type of event, and the volume of both social media discussion and traditional media coverage all had significant impacts on the duration. Our findings provide practical implications for the carrying out of targeted and stage-based governance of public opinions.

Objective: We sought to understand the status of promotion pressure among university teachers in China. This study explored the promotion duration and influencing factors among teachers in different disciplines of the social sciences. Methods: Using event history analysis, this study collected data regarding university teachers of China. The sample included 536 teachers who had been promoted from assistant to associate professor and 243 teachers promoted from associate to full professor. Our results revealed that the overall time required for promotion in the social sciences is relatively long. For those promoted from assistant to associate professor, the mean time for promotion was 14.155 years, with a median of 11 years, while for the transition from associate to full professor, the mean was 13.904 years with a median of nine years. Furthermore, in the survival function of the promotion duration, there is a stage pattern for both assistant to associate professor and associate to full professor. In addition, the Kaplan–Meier results showed that the mean promotion time in economics was the shortest. The Cox regression results indicated that males had a higher chance of promotion than females, and faculty members with doctoral degrees had a higher likelihood of promotion than those without. For those advancing from assistant to associate professor, the university of employment had significant positive effects on promotion. This paper provides empirical support for the current societal concerns regarding promotion pressure among university teachers.

Medical institutions face a variety of challenges as they seek to enhance their reputation and increase the influence of their social media accounts. Becoming a social media influencer in the health field in today’s complex online environment requires integrated social and technical systems. However, rather than holistically investigating the mechanism of account influence, studies have focused on a narrow subset of social and technical conditions that drive online influence. We attribute this to the mismatch between complex causality problems and traditional symmetric regression methods. In this study, we adopted an asymmetric configurational perspective that allowed us to test a causally complex model of the conditions that create strong and not-strong account influence. We used fuzzy-set qualitative comparative analysis (fsQCA) to detect the effects of varying configurations of three social system characteristics (i.e., an oncology-related attribute, a public attribute, and comment interaction) and two technical system characteristics (i.e., telepresence and video collection) on the TikTok accounts of 63 elderly Chinese doctors (60 to 92 years old). Our results revealed two pathways associated with distinct sociotechnical configurations to strong account influence and three pathways associated with distinct sociotechnical configurations to not-strong account influence. Furthermore, the results confirmed that a single antecedent condition cannot, on its own, produce an outcome, i.e., account influence. Multiple inter-related conditions are required to produce an influential account. These results offer a more holistic picture of how health science communication accounts operate and reconcile the scattered results in the literature. We also demonstrate how configurational theory and methods can be used to analyze the complexities of social media platforms.

随着互联网的逐渐普及和内容日益丰富,上网对儿童学习成绩的影响日益引起重视,但这些影响可能存在公众心目中的“第三人效果”或“假定影响”效应.基于2016年“中国家庭追踪调查”少儿问卷调查数据,采用定序逻辑斯蒂回归分析网络使用对儿童学习成绩的客观影响.研究发现,上网娱乐对儿童的语文和数学成绩均无显著影响;上网学习显著提高儿童的语文成绩,但对其数学成绩无显著影响;上网社交对儿童的语文和数学成绩均有显著负面影响.

20世纪50年代心理学家所罗门·阿希著名的视觉线段实验,是群体传播从众现象的重要研究.此后,全球众多学者对阿希的线段实验进行了验证性研究.与50年代美国个人主义文化背景下阿希实验不同的是,本研究是在互联网时代下,在以中国为代表的集体主义文化下对阿希实验进行的探索性创新研究.线下实验发现:有“大多数人”的群体压力的实验组(n=32)从众率为76％,匿名私下回答的控制组(n=25)错误率为0,与阿希实验的结果基本一致,略高于阿希2个百分点;通过统计检验,实验组和控制组有显著性差异,群体压力对个体从众有显著影响(x2=36.48,df =1,p＜0.001).线上实验发现:实验组(n=24)从众率为100％,控制组(n=25)错误率为0,线上的从众率明显高于线下;线上实验组和控制组有显著差异,互联网上群体压力对个体从众依然有显著性影响(x2=49,df=1,p＜0.001),匿名性并没有对个体的从众产生消解作用.

本文采用社会网络分析的视角和方法,以晋宁冲突事件为例,对线上集体行动的网络组织结构形态以及E-领袖的特征进行分析.分析发现,关注关系网呈现“大球+小散点”的组织结构形态;转发关系网呈现“小球+多散点+三人组”的组织结构形态;E领袖呈现“媒体+名人+普通用户”三足鼎立组合模式;草根用户异军突起,体现网络赋权;政府账号作用相对微弱.线上集体行动是与技术、政治和文化的多元互动过程,在新媒体时代线上集体行动对政府、媒体带来一定挑战,由此可见,本文也试图提出相应的对策.

数字内容产业界定 2012年,我国“国民经济和社会发展第十二个五年规划纲要”提出要加快发展文化产业,推动文化产业成为国民经济支柱型产业,增强文化产业整体实力和竞争力.同时还提出要推进文化产业结构调整,大力发展数字内容和动漫等重点文化产业.

构建媒体对外传播“四力” 在互联网时代,我国主流媒体如何构建对外传播的“四力”,讲好中国故事,是当前新时代形势下的重要议题.构建党的媒体的传播力、引导力、影响力、公信力,在当前国际传媒格局下具有重要的现实意义.

在全球报业遇冷的背景下,印度报业呈现逆势繁荣的景象.本文用具体数据说明了印度报业发展的规模和趋势,并对印度报业繁荣的原因进行了深入分析,如多语言环境、地方性语言报纸崛起、识字率提高、互联网使用率较低、广告是主要收入来源,以此希求对我国报业的发展具有一定的启示.

集体行动与媒介关系密切,大众媒介产生伊始,集体行动的成功与否很大程度上取决于对媒介的利用程度.技术的发展推动了媒介的进步,新媒体时代下,互联网丰富了集体行动的形式和内容,对集体行动产生了更加深远的影响.在分析媒介与集体行动关系的基础上对新媒体在集体行动中的作用进行探析,梳理了新媒体在世界各国集体行动中的实际运用情况和集体行动研究的新发展.

普利策新闻奖<br>　　新闻作品反映一个国家在一个时代的价值标准和社会发展状况。作为美国新闻界最高荣誉的普利策新闻奖，是现实的一面镜子，同时也折射出美国媒体的价值观，具有示范标杆作用。普利策奖是在1917年根据美国报业巨头约瑟夫·普利策的遗愿设立的，用以奖励在报纸、杂志、网络新闻（online journalism），以及文学和音乐作曲等方面取得成就的奖项。“普利策新闻奖不仅是美国近300个新闻奖中最知名的一个，而且为全世界所关注。”

随着社会化媒体向日常生活的渗透,企业逐渐重视社会化媒体营销的规划和策略.社会化媒体为传统企业营销提供了新的方式和思路.线上关系网络结构在很大程度上影响企业微博营销传播的效果.选取新浪企业微博发起的商业活动为案例进行研究,采用社会网络分析思路,可探索企业社会化媒体营销传播效果的规律.研究发现:1.粉丝密度是考察社会化媒体营销效果的重要指标;2.粉丝密度低,传播效果差;3.传播路径层级直接决定传播效果;4.KOL引流数量对于参与率没有影响;5.单纯增加粉丝数量的做法是片面的.

国际数字动漫产业发展迅速,具有广阔的市场潜力,在经济发展中发挥着越来越重要的作用.本文考察国际数字动漫产业的发展现状与趋势,总结动漫产业强国美国和日本以及动漫新兴国家印度的成功经验,提出对我国数字动漫产业发展的对策.