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1.
随着开源软件(OSS)的普及，作为其承载平台的开源软件社区，也得到了用户的广泛使用。但用户往往仅从社区获取开源软件或代码，而缺乏知识贡献的意愿，这将影响OSS社区的持续运营和发展。基于社会影响理论，本文建立了开源软件社区用户知识贡献行为模型，考察了顺从、认同、内化三种社会影响机制对用户行为的作用。研究收集了351份有效数据，采用结构方程模型(SEM)进行分析。研究结果显示，社会认可（认同机制）是影响开源软件社区用户知识贡献意愿的主要因素，群体规范（内化机制）对用户的贡献意愿没有显著作用，而主观规范（顺从机制）阻碍用户的贡献意愿形成。研究结果启示开源软件社区需重视建立用户的社会认同，从而促进其知识贡献行为，确保社区的成功。 相似文献
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同侪影响对用户贡献行为的作用研究———基于网络客观大数据的分析 《科学学研究》2021,39(12):2294-2304
本文将同侪影响引入在线创新社区的用户行为研究中,从广度和深度两方面考察同侪影响对用户贡献行为的影响,并分析感知收益的中介作用。研究以小米社区MIUI功能与讨论区的创意集市板块为对象构建S-O-R模型,采用6567名用户发布的8830条创意、5.26万条评论和收到的103.36万条评论数据,利用Mplus8.1分析检验,结果发现：同侪影响广度与深度均有利于促进用户贡献行为,综合收益在同侪影响广度、深度与用户贡献行为间起正向中介效应,情感收益仅在同侪影响广度、深度与主动贡献行为间起正向中介效应,而认知收益则在同侪影响深度与反应贡献行为间起负向中介效应。研究拓展了在线网络情境下知识管理与社会学领域的交叉研究,并为在线创新社区社交网络和知识管理提供重要启示。 相似文献
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随着现代网络的发展,登录移动社交平台已经成为大多数人每天的日常,和亲人朋友在社交平台上的交流远远多于面对面的交谈,学习工作上的事情也大多可以用社交软件完成,在这样的大前提下,移动社交平台用户之间的信任关系必然要成为关注的重点。用户信任度可以用来详细检查用户之间所有可能的社交网络关系,本文以新浪微博为例提供了一种计算用户之间信任的方法,通过对用户之间的信任进行分析完成相应的推荐和其他服务。 相似文献
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虚拟社区用户忠诚对于虚拟社区的长期可持续性发展尤为重要。本研究以知识分享行为（知识共享数量和质量）为中介变量,探讨社会资本（信任、社会联结性、共同愿景）和外部动机（互惠动机、声誉动机）对社区忠诚的作用机理,并通过结构方程模型进行验证。研究结果表明,信任和外部动机通过知识共享数量和质量对社区忠诚有显著正向影响,社会联结性仅通过知识共享数量对社区忠诚有显著影响;信任和外部动机对知识共享数量和质量有显著正向影响,社会联结性仅显著影响知识共享数量,而共同愿景对知识共享数量和质量均无显著影响;知识共享行为对社区忠诚有显著正向影响,并且知识共享质量对社区忠诚的影响更显著。该结论为企业重视虚拟社区用户知识分享行为从而吸引和留住虚拟社区用户提供了决策支持,为企业更好的运营虚拟社区并利用虚拟社区获得可持续发展提供了重要启示。 相似文献
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Micro-blogging services such as Twitter allow anyone to publish anything, anytime. Needless to say, many of the available contents can be diminished as babble or spam. However, given the number and diversity of users, some valuable pieces of information should arise from the stream of tweets. Thus, such services can develop into valuable sources of up-to-date information (the so-called real-time web) provided a way to find the most relevant/trustworthy/authoritative users is available. Hence, this makes a highly pertinent question for which graph centrality methods can provide an answer. In this paper the author offers a comprehensive survey of feasible algorithms for ranking users in social networks, he examines their vulnerabilities to linking malpractice in such networks, and suggests an objective criterion against which to compare such algorithms. Additionally, he suggests a first step towards “desensitizing” prestige algorithms against cheating by spammers and other abusive users. 相似文献
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Andrea L. Kavanaugh Debbie Denise Reese John M. Carroll Mary Beth Rosson 《The Information Society》2013,29(2):119-131
Communities with high levels of social capital are likely to have a higher quality of life than communities with low social capital. This is due to the greater ability of such communities to organize and mobilize effectively for collective action because they have high levels of social trust, dense social networks, and well-established norms of mutuality (the major features of social capital). Communities with “bridging” social capital (weak ties across groups) as well as “bonding” social capital (strong ties within groups) are the most effective in organizing for collective action. People who belong to multiple groups act as bridging ties. When people with bridging ties use communication media, such as the Internet, they enhance their capability to educate community members and to organize, as needed, for collective action. This article summarizes evidence from stratified household survey data in Blacksburg, VA, showing that people with weak (bridging) ties across groups have higher levels of community involvement, civic interest, and collective efficacy than people without bridging ties among groups. Moreover, heavy Internet users with bridging ties have higher social engagement, use the Internet for social purposes, and have been attending more local meetings and events since going online than heavy Internet users with no bridging ties. These findings may suggest that the Internet—in the hands of bridging individuals–is a tool for enhancing social relations and information exchange, and for increasing face-to-face interaction, all of which help to build both bonding and bridging social capital in communities. 相似文献
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Andrea L. Kavanaugh Debbie Denise Reese John M. Carroll Mary Beth Rosson 《The Information Society》2005,21(2):119-131
Communities with high levels of social capital are likely to have a higher quality of life than communities with low social capital. This is due to the greater ability of such communities to organize and mobilize effectively for collective action because they have high levels of social trust, dense social networks, and well-established norms of mutuality (the major features of social capital). Communities with “bridging” social capital (weak ties across groups) as well as “bonding” social capital (strong ties within groups) are the most effective in organizing for collective action. People who belong to multiple groups act as bridging ties. When people with bridging ties use communication media, such as the Internet, they enhance their capability to educate community members and to organize, as needed, for collective action. This article summarizes evidence from stratified household survey data in Blacksburg, VA, showing that people with weak (bridging) ties across groups have higher levels of community involvement, civic interest, and collective efficacy than people without bridging ties among groups. Moreover, heavy Internet users with bridging ties have higher social engagement, use the Internet for social purposes, and have been attending more local meetings and events since going online than heavy Internet users with no bridging ties. These findings may suggest that the Internet—in the hands of bridging individuals-is a tool for enhancing social relations and information exchange, and for increasing face-to-face interaction, all of which help to build both bonding and bridging social capital in communities. 相似文献
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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
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日益兴起的社会网络负功能研究,修正了以往过度重视积极效应的认识误区,逐渐成为社会网络研究的核心话题。本文基于企业层面,对相关领域的文献进行总结梳理后发现,企业社会网络的负功能可作用于微观、中观和宏观三个层面,分别表现为限制组织成员的创造力、导致企业面临"负债"困境、促使市场分割与地方保护主义的形成。在影响因素的研究中,现有的分析框架可归纳为网络结构主义和组织环境两种理论视角,网络排他性、过度嵌入、市场需求的不确定性、技术动荡、企业生命周期与战略目标均对社会网络负功能的发生产生重要作用。在此基础上,本文从研究视角、内容、方法和理论建构四个方面提出未来研究的发展方向。 相似文献
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《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
11.
As network analysis methods prevail, more metrics are applied to co-word networks to reveal hot topics in a field. However, few studies have examined the relationships among these metrics. To bridge this gap, this study explores the relationships among different ranking metrics, including one frequency-based and six network-based metrics, in order to understand the impact of network structural features on ranking themes on co-word networks. We collected bibliographic data from three disciplines from Web of Science (WoS), and generated 40 simulation networks following the preferential attachment assumption. Correlation analysis on the empirical and simulated networks shows strong relationships among the metrics. Their relationships are consistent across disciplines. The metrics can be categorized into three groups according to the strength of their correlations, where Degree Centrality, H-index, and Coreness are in one group, Betweenness Centrality, Clustering Coefficient, and frequency in another, and Weighted PageRank by itself. Regression analysis on the simulation networks reveals that network topology properties, such as connectivity, sparsity, and aggregation, influence the relationships among selected metrics. In addition, when comparing the top keywords ranked by the metrics in the three disciplines, we found the metrics exhibit different discriminative capacity. Coreness and H-index may be better suited for categorizing keywords rather than ranking keywords. Findings from this study contribute to a better understanding of the relationships among different metrics and provide guidance for using them effectively in different contexts. 相似文献
12.
《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
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在大学生创业活动中,各成员之间通过信息转移这一行为建立纵横交错的联系,形成信息转移网络,具有小世界网络模型特征。本文用小世界网络模型分析大学生创业活动,并用特征路径长度和集团化系数来表征大学生创业活动网络节点之间信息转移频率和集聚程度,从而为促进大学生创业活动的发展提供一种新的思路。 相似文献
15.
Michel Laroche Mohammad Reza Habibi Marie-Odile Richard 《International Journal of Information Management》2013
There is an ongoing debate over the activities of brands and companies in social media. Some researchers believe social media provide a unique opportunity for brands to foster their relationships with customers, while others believe the contrary. Taking the perspective of the brand community building plus the brand trust and loyalty literatures, our goal is to show how brand communities based on social media influence elements of the customer centric model (i.e., the relationships among focal customer and brand, product, company, and other customers) and brand loyalty. A survey-based empirical study with 441 respondents was conducted. The results of structural equation modeling show that brand communities established on social media have positive effects on customer/product, customer/brand, customer/company and customer/other customers relationships, which in turn have positive effects on brand trust, and trust has positive effects on brand loyalty. We find that brand trust has a fully mediating role in converting the effects of enhanced relationships in brand community to brand loyalty. The implications for marketing practice and future research are discussed. 相似文献
16.
《Research Policy》2023,52(8):104844
Compared to senior scientists, early-career scientists have largely been neglected in the literature on academic success. This study aims to identify the effects of local peer communities of Ph.D. candidates on their future careers. We argue that local communities of Ph.D. candidates may offer both supportive and competitive environments depending on the nature of the relationships between its members. While Ph.D. candidates generally learn from and support each other in their local peer communities, they may also compete for their mentor's attention and future academic positions. We analyse such complex peer effects for 90,264 Ph.D. candidates in the field of mathematics in a genealogical way, by measuring a candidate's academic career success by the number of next-generation Ph.D. candidates supervised later on. To capture both the supportive and competitive peer effects, we distinguish between local peers who share mentors (co-mentees) and other local peers. Our result suggests that competition exists primarily among peers who share mentors, and only at the start of one's career. We also find supportive effects among peers who do not share mentors, particularly those from the same cohort. Our results highlight the importance of universities supporting informal interactions among Ph.D. candidates. 相似文献
17.
国内外普遍认为高校及科研院所的科研人员与企业的合作有助于推动国家创新,但迄今尚少有经验研究来探讨校企合作究竟对科研活动产生了哪些积极的或消极的影响。本文基于对一项全国七千余名科研人员的调查数据的分析,全面考察了科研人员承担企业项目对于科研文化、科研网络、科研投入及产出等多方面的具体影响,研究发现承担企业项目的科研人员有更高的研究积极性、建立了更广泛的科研合作网络、在科研成果的市场转换方面表现也更好,但同时也发现承担企业项目对科研文化和基础研究可能存在不利影响。研究结果为我们更好地促进科研机构与企业协同创新提供了新的启示。 相似文献
18.
网络整体结构与合作强度对创新绩效的影响 《科学学研究》2023,41(1):168-180
发现协同创新网络类型、分析网络整体结构特征及其创新绩效影响因素，为提高协同合作效率具有重要的现实意义。基于协同创新视角，以新能源汽车技术的共同专利权人为研究对象，用Louvain算法识别协同创新网络。根据网络整体结构特征，用K-means聚类算法划分协同创新网络类型，并深入分析每种网络。用专利数量和专利质量衡量网络创新绩效，以合作强度和网络整体结构特征为条件属性，网络创新绩效为决策属性，用CART决策树分析创新绩效的影响关系。新方法以数据驱动为视角，借助数据挖掘技术深入剖析网络结构特征、合作强度和创新绩效之间的非线性知识规则。研究结果表明：(1)共有四种协同创新网络，即二元协同创新网络、星型协同创新网络、完全协同创新网络和复杂协同创新网络，不同网络类型的整体结构特征和创新绩效差异化明显，证实了分类讨论的合理性与科学性。(2)二元协同创新网络和完全协同创新网络没有明显的核心成员，星型协同创新网络和复杂协同创新网络存在核心成员。(3)在不受其他因素的共同影响下，复杂协同创新网络和星型协同创新网络的合作强度分别对网络创新绩效具有正向和负向影响；在二元协同创新网络中，过高或过低的合作强度均有助... 相似文献
19.
News source evaluations based on fact-checking can help curb the consumption and spread of fake news on social media. Prior research has primarily considered source evaluations with intuitive icons that indicate whether or not news sources are reputable. But can we increase the power of these icons by adding more detailed information about the evaluation that explains the reasons for the icon? What additional benefit would such evaluation details bring? Would they have the same effect for both positive and negative evaluations? We conducted two online experiments to understand the effects of a source evaluation icon (a positive or negative summary of the evaluation) and more detailed evaluation information explaining the reasons for the icon. Our results show an asymmetric effect of positive and negative icons and details. Negative icons reduced the believability of the articles, but adding evaluation details supporting the icon had no additional effect. In contrast, positive icons had no significant effects, but adding evaluation details significantly increased believability. We also found that users were more likely to view the evaluation details when the content of the article aligned with their pre-existing opinions, but the valence of the icon (positive or negative) did not affect this decision. 相似文献
20.
《Information processing & management》2022,59(1):102785
Internet platforms increasingly rely on personal data to maintain user base and attract potential users. However, users might misrepresent their personal information in response to the requests when they expect their personal information to be used for unstated purposes. Misrepresenting of personal information (MPI), as a regular deviant behavior on online platforms, leads to data noises and service failures and needs further investigation. Drawing on the neutralization theory and online scenario survey, this study constructs a model to examine the factors of MPI. The results show that techniques of neutralization, such as denial of injury, defense of necessity, metaphor of the ledger, and avoidance of greater harm, are positively associated with users’ intention of MPI. In particular, avoidance of greater harm has a stronger effect on MPI intention than other neutralization techniques. Furthermore, we also explore the contingent role of personality traits. The results show that extraversion negatively moderates the relationships between denial of injury, avoidance of greater harm and MPI, whereas neuroticism plays a positive role in moderating the relationships between denial of injury, metaphor of the ledger, avoidance of greater harm and MPI. Moreover, post-hoc analysis results show that users do some differernces regarding justify their deviant disclosure behavior by using neutralization techniques between e-commerce platform and social networking site. Focusing on the dark side of disclosure behavior, this study enriches the current literature by applying neutralization theory and provides a new direction for academia and Internet practitioners to understand users’ deviant disclosure behavior. 相似文献