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1.
《Information processing & management》2022,59(1):102769
This study aims at helping people recognize health misinformation on social media in China. A scheme was first developed to identify the features of health misinformation on social media based on content analysis of 482 pieces of health information from WeChat, a social media platform widely used in China. This scheme was able to identify salient features of health misinformation, including exaggeration/absolutes, induced text, claims of being unique and secret, intemperate tone or language, and statements of excessive significance and likewise. The scheme was then evaluated in a user-centred experiment to test if it is useful in identifying features of health misinformation. Forty-four participants for the experimental group and 38 participants for the control group participated and finished the experiment, which compared the effectiveness of these participants in using the scheme to identify health misinformation. The results indicate that the scheme is effective in terms of improving users’ capability in health misinformation identification. The results also indicate that the participants’ capability of recognizing misinformation in the experimental group has been significantly improved compared to those of the control group. The study provides insights into health misinformation and has implications in enhancing people's online health information literacy. It informs the development of a system that can automatically limit the spread of health misinformation. Moreover, it potentially improves users’ online health information literacy, in particular, under the circumstances of the COVID-19 pandemic. 相似文献
2.
《Information processing & management》2023,60(2):103228
The phenomenal spread of fake news online necessitates further research into fake news perception. We stress human factors in misinformation management. This study extends prior research on fake news and media consumption to examine how people perceive fake news. The objective is to understand how news categories and sources influence individuals' perceptions of fake news. Participants (N = 1008) were randomly allocated to six groups in which they evaluated the believability of news from three categories (misinformation, conspiracy, and correction news) coupled with six online news sources whose background (official media, commercial media, and social media) and expertise level varied (the presence or absence of a professional editorial team). Our findings indicated people could distinguish media sources, which have a significant effect on fake news perception. People believed most in conspiracy news and then misinformation included in correction news, demonstrating the backfire of correction news. The significant interaction effects indicate people are more sensitive to misinformation news and show more skepticism toward misinformation on social media. The findings support news literacy that users are capable to leverage credible sources in navigating online news. Meanwhile, challenges of processing correction news require design measures to promote truth-telling news. 相似文献
3.
[目的/意义] 从动机、机会、能力3个维度揭示学术社交网络用户知识共享意愿的影响因素。[方法/过程] 基于MOA理论,构建学术社交网络用户知识共享意愿影响因素模型,搜集数据并采用结构方程模型方法对模型研究假设进行验证。[结果/结论] 利他动机、声誉动机、社区认同动机、知识获取动机、信息质量、系统质量、自我效能对学术社交网络用户的知识共享意愿影响显著,社交关系动机、服务质量对学术社交网络用户的知识共享意愿影响并不显著。该模型对解释我国学术社交网络用户的知识共享意愿和指导学术社交平台建设具有指导意义。 相似文献
4.
During crises, there is a need for a large amount of information in a short period. Such need creates the base for misinformation to spread within and outside the affected community. This may result in misinformation harms that can generate serious short term or long-term consequences. In such situations, there is a need for a joint human-machine effort to mitigate misinformation. Though there has been research in the area of management of AI in the recent past, there has been scarce work in examining situations where machines and humans interact for mitigating misinformation. In order to systematically analyze misinformation and suggest mechanisms for mitigation, we draw on Activity Theory to conceptualize a suitable framework. Such a framework will enable investigating human-machine interactions through loops of “misinformation generation” and “misinformation mitigation” activities for mitigating misinformation harms. The paper also validates the framework using three different target audiences, undergraduates, graduates and professionals. 相似文献
5.
《Information processing & management》2022,59(1):102740
One of the most time-critical challenges for the Natural Language Processing (NLP) community is to combat the spread of fake news and misinformation. Existing approaches for misinformation detection use neural network models, statistical methods, linguistic traits, fact-checking strategies, etc. However, the menace of fake news seems to grow more vigorous with the advent of humongous and unusually creative language models. Relevant literature reveals that one major characteristic of the virality of fake news is the presence of an element of surprise in the story, which attracts immediate attention and invokes strong emotional stimulus in the reader. In this work, we leverage this idea and propose textual novelty detection and emotion prediction as the two tasks relating to automatic misinformation detection. We re-purpose textual entailment for novelty detection and use the models trained on large-scale datasets of entailment and emotion to classify fake information. Our results correlate with the idea as we achieve state-of-the-art (SOTA) performance (7.92%, 1.54%, 17.31% and 8.13% improvement in terms of accuracy) on four large-scale misinformation datasets. We hope that our current probe will motivate the community to explore further research on misinformation detection along this line. The source code is available at the GitHub.2 相似文献
6.
在线的C2C分享平台是目前分享经济的重要方向之一。一些C2C知识分享平台中采用对成员的评价机制作为鼓励分享行为的重要手段之一,但是在理论上评价机制与个体知识分享行为之间的关联机制却少有研究。本文通过内容分析和社会网络分析等方法,对国内一个咨询行业专业QQ群进行了大数据分析,实证探讨了系统评价和群内成员互评两种评价机制在成员的知识分享行为与个体知识网络中心性之间的调节效应。在实证分析的基础上,本文进一步根据系统评价和成员互评两种评价机制作用的异同将知识分享平台划分为应用型、创新型和合作型知识分享平台。 相似文献
7.
《Information processing & management》2019,56(4):1565-1575
People who are suspected to suffer mental disorders often explore online communities to gather medical information. Such medical information benefits these people by facilitating self-diagnosis and social support for the mental disorders. At the same time, however, misinformation can aggravate mental disorders and worsen psychological status. Focusing on two representative mental illnesses, bipolar and depressive disorders, this study analyzed how users shared their experiences with illness and provided advice. Postings for bipolar and depressive disorders were gathered from subreddit communities and used for semantic network analysis. Results showed that users in both communities described sleep disorder episodes and financial problems with negative emotional expressions. Users in the bipolar disorder community showed more interest in the topic of medication, whereas users in the depressive disorder community were more interested in suicide issues. We discuss how these properties in the subreddit communities can be applied to understand user experiences of bipolar and depressive disorders. 相似文献
8.
[目的/意义]探索微信用户对于微信平台上传播的健康信息的辨别能力,以及此类信息对其产生的效用。[方法/过程]问卷调查法及描述性统计方法,在权威平台上抽取真实/虚假健康信息,并结合“获得信息→判断真假→产生行为”的问题设计模式构成问卷,进行纸质和网络调查。[结果/结论]接受调查的大多数微信用户缺乏准确识别健康信息真伪的能力,公民健康素养的提高任重而道远;微信是健康信息传播的有效平台,但也为虚假健康信息的传播提供了“肥沃的土壤”,且用户并未认识到其信息辨别能力中存在的问题,即使对虚假的健康信息产生了错误的判断,大多数用户的“活跃性”也会导致这类信息仍然被广泛传播。 相似文献
9.
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
10.
[目的/意义]分析通证知识社区的知识分享网络结构,有助于把握区块链背景下的虚拟社区知识分享和传播规律。[方法/过程]以国内通证知识社区代表——币乎网为研究对象,通过网络爬虫方式获取币乎用户样本数据,采用社会网络分析和内容分析方法,运用UCINET工具对社区用户的知识分享网络进行网络特征分析。[结果/结论]样本网整体呈现出小世界效应和无标度网络特征;中心性高的核心用户对社区知识贡献和传播的影响力较高;通证激励有助于挖掘社区中的优质内容。 相似文献
11.
移动互联网的发展为微博的发展提供了更加广阔的发展空间,以复杂网络的基本统计特性为基础,通过抓取新浪微博中的相关数据,对其进行处理分析,详细分析微博用户在信息发布行为、信息发布内容方面的相关特性以及用户的关注行为和评论转发行为进行了详细地分析,认为微博网络是典型的小世界网络,微博网络整体密度较小,呈稀疏状态,但局部密集;微博网络用户的分布呈不均匀的状态,用户在信息发布、分享等方面存在较大的信息不对称性,只有小部分用户拥有较多的信息资源,扮演核心角色,大部分用户在微博中处于边缘地位。这为微博营销和微博舆论引导与消解提供了基础。 相似文献
12.
《Information processing & management》2020,57(3):102127
This conceptual paper focuses on misinformation in the context of asylum seekers. We conducted a literature review on the concept of misinformation, which showed that a more nuanced understanding of information and misinformation is needed. To understand and study different viewpoints when it comes to the perception of the accuracy of information, we introduce two new concepts: perceived misinformation and normative misinformation. The concepts are especially helpful when marginalised and vulnerable groups are studied, as these groups may perceive information differently compared to majority populations. Our literature review on the information practices of asylum seekers shows that asylum seekers come across different types of misinformation. These include official information that is inadequate or presented inadequately, outdated information, misinformation via gatekeepers and other mediators, information giving false hope or unrealistic expectations, rumours and distorted information. The diversity of misinformation in their lives shows that there is a need to understand information in general in a broad and more nuanced way. Based on this idea, we propose a Social Information Perception model (SIP), which shows that different social, cultural and historical aspects, as well as situation and context, are involved in the mental process which determines whether people perceive information as accurate information, misinformation or disinformation. The model, as well as the concepts of perceived and normative misinformation, are helpful when the information practices of marginalised and vulnerable groups are studied, giving a holistic view on their information situation. Understanding the information practices more holistically enables different actors to give trustworthy information in an understandable and culturally meaningful way to the asylum seekers. 相似文献
13.
虚拟社区为人们提供了一个更开放和更方便的信息交流平台,是近年来国内外学者研究的一个热点问题。论文从虚拟社区的信息交流和知识共享、用户行为以及商业应用这3个方面对虚拟社区的研究现状进行了分析,同时指出了虚拟社区研究存在的问题以及未来的研究方向:在信息传播和知识共享方面,深入挖掘虚拟社区信息传播和知识共享模式,同时制定有效的引导机制;在用户行为方面,加强对如何利用虚拟社区推进社会健康、和谐的发展这方面的研究;在商业应用方面,微博的商业价值需要深入探索。 相似文献
14.
微信群已成为隐性知识传播的重要平台,但鲜有研究探讨微信群中隐性知识的传播规律。本文基于复杂网络与传播动力学理论研究了微信群中隐性知识的传播机理,建立了微信群中隐性知识的传播模型,推导出了区分隐性知识在微信群中传播与否的阈值条件,验证了传播阈值始终是一个有限数,并对隐性知识传播过程进行了数值模拟。结果表明,微信群的网络结构对隐性知识传播有重要影响,隐性知识在无标度网络中的传播速度比在均匀网络中更快,传播阈值与最终传播规模更大。研究还表明,只要根据阈值条件将有共享意愿的用户数量与有知识吸收能力的用户数量增加到相应的临界值以上,隐性知识就会在微信群中传播。最后对研究结论和未来研究方向进行了讨论。 相似文献
15.
本文通过分析互联网开放式创新社区用户参与创新行为，采集用户知识共享的不同特征数据，构建用户画像，从而识别不同类别用户参与平台知识创新的功能和角色。此外，基于用户的异质性，分析不同用户群体的创新需求差异和需求点的分布。通过对小米社区的实证研究识别出了核心用户、积极创新用户、积极社交用户、潜在创意用户、边缘用户这5个类型用户并进行画像，同时从必备型需求、魅力型需求、期望型需求、沉默型需求这4个角度对不同类型用户的创新需求点进行分析，体现了不同类型用户的不同创新需求差异。通过用户画像构建以及用户创新需求识别，达到社区管理与用户之间的高匹配度及用户的创新需求与企业产品创新方向之间的一致性。 相似文献
16.
SOLOMO是一种融合社交、本地和移动3种服务的新型社会化交流网络,是未来互联网发展的重要驱动力量,其意味着泛在知识环境环境的到来,深刻影响着知识创造、传播和利用的方式。文章在分析SOLOMO环境下信息资源建设特征的基础上,提出信息资源协同建设是第三代图书馆在泛在知识环境下实现信息互联共享的根本途径,并从图书馆与用户,图书馆与图书馆以及图书馆与信息供应链上其他机构3个角度深入研究资源协同建设内容,以便提升图书馆资源供应能力,在泛在知识环境下为用户提供互联、高效、便利的信息资源保障。 相似文献
17.
【目的/意义】视频分享平台意见领袖在信息传递、舆论引导及促进多媒体平台发展等方面发挥着重要作
用,对其特征和形成路径的研究可促进视频分享平台优质用户的形成,推动视频资源创作和分享生态的构建。【方
法/过程】采集视频分享平台百大意见领袖的视频资源数据,剖析其创作及影响力特征,并在构建视频质量评价指
标体系和对视频质量评价分析的基础上,通过聚类分析揭示意见领袖形成路径。【结果/结论】研究表明,目前单一
型和交叉型意见领袖较多;视频分享平台意见领袖通常以用户需求为导向,对大众化、题材多、易制作的内容更具
创作偏好;其影响程度和影响范围表现出较强的正相关性。此外,意见领袖形成路径可概括为全明星型、达人型、
活跃型、不稳定型4种,其中达人型意见领袖形成路径最为用户所偏好。【创新/局限】本文结合意见领袖创作视频质
量评价体系的构建,揭示视频分享平台意见领袖的形成路径,相关路径有待进一步跟踪验证。 相似文献
18.
《Information processing & management》2020,57(2):102025
Over the recent years, the growth of online social media has greatly facilitated the way people communicate with each other. Users of online social media share information, connect with other people and stay informed about trending events. However, much recent information appearing on social media is dubious and, in some cases, intended to mislead. Such content is often called fake news. Large amounts of online fake news has the potential to cause serious problems in society. Many point to the 2016 U.S. presidential election campaign as having been influenced by fake news. Subsequent to this election, the term has entered the mainstream vernacular. Moreover it has drawn the attention of industry and academia, seeking to understand its origins, distribution and effects.Of critical interest is the ability to detect when online content is untrue and intended to mislead. This is technically challenging for several reasons. Using social media tools, content is easily generated and quickly spread, leading to a large volume of content to analyse. Online information is very diverse, covering a large number of subjects, which contributes complexity to this task. The truth and intent of any statement often cannot be assessed by computers alone, so efforts must depend on collaboration between humans and technology. For instance, some content that is deemed by experts of being false and intended to mislead are available. While these sources are in limited supply, they can form a basis for such a shared effort.In this survey, we present a comprehensive overview of the finding to date relating to fake news. We characterize the negative impact of online fake news, and the state-of-the-art in detection methods. Many of these rely on identifying features of the users, content, and context that indicate misinformation. We also study existing datasets that have been used for classifying fake news. Finally, we propose promising research directions for online fake news analysis. 相似文献
19.
20.
Fattane Zarrinkalam Mohsen Kahani Ebrahim Bagheri 《Information processing & management》2018,54(2):339-357
Inferring users’ interests from their activities on social networks has been an emerging research topic in the recent years. Most existing approaches heavily rely on the explicit contributions (posts) of a user and overlook users’ implicit interests, i.e., those potential user interests that the user did not explicitly mention but might have interest in. Given a set of active topics present in a social network in a specified time interval, our goal is to build an interest profile for a user over these topics by considering both explicit and implicit interests of the user. The reason for this is that the interests of free-riders and cold start users who constitute a large majority of social network users, cannot be directly identified from their explicit contributions to the social network. Specifically, to infer users’ implicit interests, we propose a graph-based link prediction schema that operates over a representation model consisting of three types of information: user explicit contributions to topics, relationships between users, and the relatedness between topics. Through extensive experiments on different variants of our representation model and considering both homogeneous and heterogeneous link prediction, we investigate how topic relatedness and users’ homophily relation impact the quality of inferring users’ implicit interests. Comparison with state-of-the-art baselines on a real-world Twitter dataset demonstrates the effectiveness of our model in inferring users’ interests in terms of perplexity and in the context of retweet prediction application. Moreover, we further show that the impact of our work is especially meaningful when considered in case of free-riders and cold start users. 相似文献