Social bots and mass media manipulated public opinion through dual opinion climate

Opinion dynamics models based on the multi-agent method commonly assume that interactions between individuals in a social network result in changes in their opinions.However,formation of public opinion in a social network is a macroscopic statistical result of opinions of all expressive individuals(corresponding to silent individuals).Therefore,public opinion can be manipulated not only by changing individuals'opinions,but also by changing their states of expression(or silence)which can be interpreted as the phenomenon"spiral of silence"in social psychology.Based on this theory,we establish a"dual opinion climate"model,involving social bots and mass media through a multi-agent method,to describe mechanism for manipulation of public opinion in social networks.We find that both social bots(as local variables)and mass media(as a global variable)can interfere with the formation of public opinion,cause a significant superposition effect when they act in the same direction,and inhibit each other when they act in opposite directions.

Online Public Opinion Guidance Strategy for College Students in the Era of We Media

In the era of We Media, online public opinion in colleges and universities has become an important front of ideological and political, with some characteristics such as concealment, diversity and sensitivity, interaction and immediacy of communication. It is urgent to carry out some researches about network public opinion analysis and guidance mechanism. It is a new challenge that the ideological and political education in colleges and universities, must face how to guide online public opinion effectively. The team building should be strengthened and the right of public opinion should be returned. The platform construction should be enriched, and it is important to give the chance to various media. Therefore, it should strengthen the mechanism construction, and public opinion guidance must be scientific and professional. Colleges and universities should build a clear network space from such aspects as the construction of network public opinion guidance institutions, the cultivation of opinion leaders, the perfection of early warning mechanism, the improvement of university network literacy and the guidance of campus media.

“If We Only Knew How You Feel”—A Comparative Study of Automated vs. Manual Classification of Opinions of Customers on Digital Media

The Web development has drastically changed the human interaction and communication, leading to an exponential growth of data generated by users in various digital media. This mass of data provides opportunities for understanding people’s opinions about products, services, processes, events, political movements, and organizational strategies. In this context, it becomes important for companies to be able to assess customer satisfaction about their products or services. One of the ways to evaluate customer sentiment is the use of Sentiment Analysis, also known as Opinion Mining. This research aims to compare the efficiency of an automatic classifier based on dictionary with the classification by human jurors in a set of comments made by customers in Portuguese language. The data consist of opinions of service users of one of the largest Brazilian online employment agencies. The performance evaluation of the classification models was done using Kappa index and a Confusion Matrix. As the main finding, it is noteworthy that the agreement between the classifier and the human jurors came to moderate, with better performance for the dictionary-based classifier. This result was considered satisfactory, considering that the Sentiment Analysis in Portuguese language is a complex task and demands more research and development.

Political Optimizer with Probabilistic Neural Network-Based Arabic Comparative Opinion Mining

Opinion Mining(OM)studies in Arabic are limited though it is one of the most extensively-spoken languages worldwide.Though the interest in OM studies in the Arabic language is growing among researchers,it needs a vast number of investigations due to the unique morphological principles of the language.Arabic OM studies experience multiple challenges owing to the poor existence of language sources and Arabic-specific linguistic features.The comparative OM studies in the English language are wide and novel.But,comparative OM studies in the Arabic language are yet to be established and are still in a nascent stage.The unique features of the Arabic language make it essential to expand the studies regarding the Arabic text.It contains unique featuressuchasdiacritics,elongation,inflectionandwordlength.Thecurrent study proposes a Political Optimizer with Probabilistic Neural Network-based Comparative Opinion Mining(POPNN-COM)model for the Arabic text.The proposed POPNN-COM model aims to recognize comparative and non-comparative texts in Arabic in the context of social media.Initially,the POPNN-COM model involves different levels of data pre-processing to transform the input data into a useful format.Then,the pre-processed data is fed into the PNN model for classification and recognition of the data under different class labels.At last,the PO algorithm is employed for fine-tuning the parameters involved in this model to achieve enhanced results.The proposed POPNN-COM model was experimentally validated using two standard datasets,and the outcomes established the promising performance of the proposed POPNN-COM method over other recent approaches.

角色演变视角下辟谣信息对社交媒体意见领袖形成的影响——基于舆论领导法则

[目的/意义]探究辟谣信息对社交媒体用户的影响,特别是对意见领袖形成现象机制的挖掘。构建社交媒体用户角色演变行为模型,研究人员可以更好地了解意见领袖的形成原因,刻画辟谣信息对社交媒体用户的作用机制,有助于对参与辟谣的“准意见领袖”进行合理引导,以提高社交媒体舆情管理的效率和准确性。[方法/过程]首先,对微博社交媒体平台中的特定主题事件进行跟踪,识别并筛选出“新生意见领袖”群体,并利用质性访谈对此群体进行深度访谈。然后,基于程序化扎根理论方法,利用NVivo 12软件进行扎根编码构建模型,并通过理论饱和度检验验证模型的完整性。最后,对社交媒体用户角色演变的原因进行深入分析和探讨。[结果/结论]在辟谣信息作用下,个体主观因素、社会环境因素和辟谣信息因素对一般用户向新生意见领袖的演变行为产生重要影响,其中个体主观因素在辟谣信息的作用下对意见领袖形成的影响更加显著,自我认知清晰、高情绪需求且情绪稳定的个体更容易成为影响力持久的意见领袖;社会公众认可、实质性奖励和政策法律支持共同构成社会环境因素,是意见领袖形成的重要保障;辟谣信息因素中的辟谣信息热度、可信度和发布质量等方面都会直接影响“潜在意见领袖”用户群体对辟谣事件的把握,进而干预其参与辟谣的决定。

支持或反对:社交媒体用户观点的形成机理

探究社交媒体用户观点形成机理,揭示影响网民观点形成的重要因素,可深入理解网络用户的行为模式,洞察网络舆论本质。文章以“双减”话题微博数据为数据源,基于主题模型和机器学习的情感分析方法挖掘用户观点;从意见氛围、社交关系、前期行为特征和用户属性等维度构造特征变量,基于LightGBM建立不同主题下的情感预测模型,采用SHapley Additive exPlanations(SHAP)对特征重要性进行排序,发现影响网民观点形成的重要因素。研究发现:前期行为特征对用户观点形成的影响最大,意见氛围次之,社交关系即好友关系影响较弱;个体在情感倾向上更易跟随规模较大的传播主体,而不是崇拜权威。

Supervision of Public Opinion under the Background of Social Co-governance-Take the Changsheng Vaccine Incident as an Example

Objective To provide reference for the news media to give play to the role of public opinion supervision in time based on the background of drug safety and social co-governance.Methods The method of case analysis was used to make a retrospective study on the Changsheng vaccine incident in 2018.Then the role of mainstream media,pharmaceutical media,and self-media in the supervision of public opinion was investigated.Results and Conclusion Both mainstream and pharmaceutical media played an excellent role in supervising the Changchun Changsheng vaccine incident.However,the content published by some pharmaceutical media was hard to understand by ordinary people.Besides,the role of self-media in public opinion supervision was polarized.Some self-media closely kept pace with mainstream media in public opinion supervision.Other self-media unilaterally pursued the click rate,publishing false information to guide wrong public opinion.The news media should optimize the supervision efficiency of drug safety.On the one hand,pharmaceutical media should pay attention to the fact that readers may not understand the difficult terms because they are not professional.On the other hand,self-media practitioners should improve their professional quality so that they will not publish some fake news to mislead public opinion.

构建新媒体环境下舆论控制的新模式——基于微博舆情事件控制的案例分析

新媒体环境下,新闻传播模式由单向式的传播变成多维、立体、几何式的传播,导致媒体格局、传播模式以及舆论生态与传统媒体环境下新闻传播不同,新闻舆论工作面临新的挑战。以微博热点为例,对几个典型舆论案例进行分析。针对新媒体环境下微博舆论传播的特点及现实困境,从舆论主体、舆论话语权掌握、舆论传播渠道、舆论传播环境四个方面出发,建构“回应—引导—联动—法治”微博的舆论控制新模式。

场域理论视角下高校网络舆情治理的防范困境与实践进路

作为意识形态工作的前沿阵地,高校肩负着培育时代新人的重大使命,是国内外各种社会思潮交锋和与西方敌对势力争夺青年一代的重要场所。在场域理论视角下,针对网络舆情治理面临的场域壁垒下的治理角色转化、资本制约下的治理权力更迭和惯习固化下的治理手段改变等危机风险,高校需在初始传播阶段建立健全舆情监测机制,构建动因性应对机制;在爆发扩散阶段强化精准研判控制局势,构建资源性保障机制;在逐渐消退阶段加强社会各界沟通协作,构建进路性导引机制。

新媒体平台中警察执法短视频传播:问题与改进——以抖音为例

近年来,警察执法短视频在以抖音为代表的新媒体视讯视频平台中大量流传并不时成为社会关注焦点,这给公安工作带来新机遇与新挑战。在开创公安普法与犯罪预防宣传新渠道的同时,个别警察执法短视频在新媒体平台传播中所暴露出的问题也给公安形象带来了消极影响。研究发现,警察执法短视频中当事人合法个人隐私保护有待加强,警察执法短视频评论区留言缺乏积极的舆论引导,个别警察执法短视频中因关键信息缺失导致民众误解,个别民警执法行为不当引发舆论危机。为此,各级公安机关在警察执法短视频制作与传播中应依法保护当事人的合法隐私免受媒体传播侵害,主动加强警察执法短视频传播中的相关舆情引导,提高警察执法短视频专业制作水准,规范与完善警察执法短视频制作与发布制度,增强民警镜头下依法、合理、得当使用警务技战术的实战能力,以推进公安机关执法规范化与自身形象建设,契合新时代公安工作的新要求。

跨社交媒体舆情风险感知:理论框架的构建与实现

社交媒体间的摇摆和迁徙使网民获取信息的方式更加复杂多样,提高舆情传播效率的同时,也加速了舆情风险的生成和演化,及时捕捉和预测网络舆情风险对维护网络安全至关重要。目前,舆情风险的感知对象主要侧重于单一社交媒体,对跨社交媒体舆情风险感知的理论框架构建及实现仍然存在拓展空间。因此,本研究通过分析跨社交媒体舆情风险的传播特征,系统构建了跨社交媒体舆情风险感知框架,具体包括三个阶段:单一媒体异常舆情识别、跨社交媒体舆情风险研判以及跨社交媒体舆情风险预测。通过构建不同阶段指标体系及数据关联挖掘,实现了跨社交媒体风险舆情的识别、研判与预测。不仅能够拓宽舆情风险感知的研究视角、丰富舆情风险理论体系,而且能够强化社交媒体赋能舆情风险治理的协同作用,有利于提高舆情风险防控水平。

社交机器人对社会舆论的影响因素研究

近年来,社交机器人已经成为人工智能领域的一个最新的研究方向。由于新冠疫情、俄乌冲突、英国脱欧等一系列重大事件中,社交机器人对公众舆论产生了重要影响,学界对社交机器人的关注度日渐升高。本文提出了基于社交机器人的社会舆论形成过程模型,分为舆论出现、争夺影响力、舆论形成3个阶段,社交机器人可以在3个阶段介入和影响。研究了社交机器人的级联效应、工作原理、影响因素,指出媒体类型、事件模糊性和争议性、受众群体等均是影响社会舆论的主要因素。调查问卷实验与案例分析表明:社交机器人对信息传播速度、网民意见/倾向的形成等具有显著影响,实验数据对今后研究具有重要参考意义。

社交网络舆情多模态知识图谱构建框架研究

[研究目的]信息技术的发展丰富了社交媒体用户的沟通交流方式,研究社交网络舆情多模态知识图谱的构建对网络舆情治理具有重要的现实意义。[研究方法]基于多模态数据的语义互补,讨论了实体属性关联、图像(视频)文字描述、图像(视频)属性、图像(视频)关联等多种异构数据融合方式。在此基础上,提出社交网络舆情多模态知识图谱的构建框架,并分析了在多模态语义理解、多模态实体对齐、多模态知识表示等方面存在的问题与挑战。[研究结论]提出基于多模态知识融合的社交网络舆情多模态知识图谱构建框架,为交互方式日趋丰富的社交网络舆情治理提供有益参考。

新型主流媒体价值引领的理蕴探究与建构路径

在党和国家高度重视媒体融合与积极壮大主流舆论阵地的背景下,推动主流媒体转型升级并强化其价值引领具有迫切性。新型主流媒体价值引领因其本质之“新”而具有生命力,因其力量之“新”而具有吸引力。新型主流媒体价值引领具有丰富的新本质规定的同时,还展现出新的强大引领力量即新传播力、新引导力、新影响力、新公信力。结合新型主流媒体价值引领的本质规定和强大力量,立足当前,构建新型主流媒体价值引领的实践路径:注重深度融合,推动主流媒体转型升级;强化主体效能,构建主体之间良性互动;创新内容生产,壮大主流舆论阵地。

媒介融合视域下意见领袖在阅读推广中的价值及提升路径

网络技术的发展为阅读推广工作构建了全新的媒介环境。媒介融合时代,意见领袖作为信息传播的桥梁,在阅读推广中发挥着特殊的作用。意见领袖不仅能帮助和引导读者提高阅读针对性、推动阅读文化的高效传播,也能引领阅读文化导向、促进文化发展繁荣。因此要提升意见领袖在阅读推广中的影响力,即:从各行各业的社会资源中挖掘、培养多元化的意见领袖资源,在双向互动中培养读者对意见领袖的情感认同,通过增强价值感知提高读者信任度,并通过持续输出优质内容塑造好阅读品牌。

“一带一路”议题全球舆论话语图景与中国应对--基于2013-2023年全球社交媒体平台X的大数据研究

[研究目的]国际社交媒体反映全球民间舆论。通过分析X(原Twitter)平台上“一带一路”相关推文,了解国际舆论对该议题的态度和反应,以提出中国应对策略。[研究方法]基于数字媒体分析方法,对近十年的相关推文进行情感分析、主题分析和社会网络分析。[研究结论]发现X平台关于“一带一路”议题的舆情的三大现状,即;关注度高,受主要相关事件影响;情感波动显著,西方主流媒体叠加负面议题;中、英文推文场域相互溢出,中国主流媒体舆论引导力不足。基于此提出三个对策,即:强化舆情风险预测,提前制定应对方案;及时回应外部关切,强化沟通与危机管理;积极设置话题,强化舆论引导与议题塑造。

基于规范中介的社交媒介使用与环保意愿研究——意见领袖特质的调节作用

在媒介融合时代,社交媒介对公众环保意愿的引导作用不言而喻。基于全国性问卷调查,本文探讨社交媒介如何通过外界的规范压力和内部的个人道德激发公众在公共领域与私人领域的环保意愿。研究表明,社交媒介使用不仅能够对公域与私域环保意愿产生促进作用,还能通过个人规范产生间接影响。高水平意见领袖特质能够正向调节主观规范在社交媒介使用和公域环保意愿间的中介作用,并且负向调节个人规范在社交媒介使用和公域、私域环保意愿间的中介作用。本研究揭示了影响社交媒介用户环保意愿的内、外部因素,并从自我视角厘清了意见领袖特质如何影响前述两种因素作用的发挥。本研究有助于在媒介融合时代背景下,探索能够更有效激发社交媒介用户环保意愿的环境宣传策略。

复杂新媒体环境中舆论导向的困境、技巧和方向

舆论导向具有决定国家政治方向、社会大局稳定、人民根本利益的极端重要性。作为一种社会需求,舆论导向涵盖导向者的社会需求和受众的社会需求两个基本向度。导向者以被导向者为前提,并依赖于其存在,忽视被导向者所处的境遇、面临的问题、需要帮助的导向,无法发挥导向作用。当前,新媒体构成要素的复杂性决定了新媒体环境的复杂性,其中的舆论较传统媒介场景中的舆论具有突发性、易变性、对抗性等特殊表征,这一方面源于舆论天然的复杂性,另一方面由新媒体环境中舆论传播链的开放性和新媒体应用场景、覆盖范围的开放性所致,归根结底是舆论生产与传播的动机出现了复杂化趋向。将复杂问题简单化处理、简单问题复杂化考量催生的“单向度舆论”“即兴式舆论”等情绪化舆论,把复杂舆论简单化引导、简单舆论复杂化导向引发的导向失灵现象,以及新媒体语境中广泛存在的社会需求,印证了复杂新媒体环境中舆论的必导性与可导性。鉴于此,舆论导向要承认、正视、适应这种复杂性,置身其中但不为喧嚣所迷惑,坚持尊重、公正、理解、互动、诚信,只有这样,导向者的导向行为才能赢得受众支持。由此而言,着眼社会需求、以人为本的导向,理应得到更多人的认可和推崇。

重大自然灾害事件中全媒体舆情风险防范的共意机制建构--以K396次列车洪灾脱险事件为例

[研究目的]超时空泛在的全媒体放大了重大自然灾害事件中的舆情风险。研究旨在探究该类舆情由危转机的机理,荟聚舆情支持力量,进而提升应急管理效能。[研究方法]以K396次列车脱险过程的舆论演进势态为研究对象,依托全形态大数据挖掘和可视化分析技术,对舆情事件演化过程进行精准描摹。基于建构主义理论,立足“要素-机制”系统分析框架,厘清“整合性共意”机制中的多元主体要素、互动关系和运行链条。[研究结论]透过重大突发自然灾害事件中舆情危机向舆情支持的个案演变过程,洞见到各司其职、共同参与的国家管理者、民众、新闻媒体和专家学者,通过“刺激发生-汇集分析-接触交流-互动回应-共意建构-决策引导”六环节,不断推动着整合性共意机制的协调运转。该研究为构筑全媒体环境下共建共治共享的国家应急管理体系提供了实践模式和理论参考。