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1.
The social question and answer (Q&A) community provides people with an effective tool to obtain high-quality information. From the perspective of reciprocal determinism and value co-creation, this study aims to investigate the formation mechanism of high-quality knowledge in the community. We develop a model to investigate how cognitive factors and community technological factors influence users’ knowledge co-creation behavior, thereby influencing knowledge quality in the community. A survey of 382 knowledge contributors in a social Q&A community shows that knowledge self-efficacy, topic richness, personalized recommendation, and social interactivity have a positive impact on users' knowledge sharing and integration behavior, which subsequently affect the community’s knowledge quality. Moreover, users' ratings moderate the influence of knowledge sharing on knowledge quality. This research demonstrates the synergistic effect of people and technology in knowledge co-creation, thus advances literature about value co-creation and content quality in online communities.  相似文献   

2.
Social question-and-answer (Q&A) sites have the potential to serve as a useful source of online information based on their content-focused and collaborative nature. Although previous research has examined various attributes of high-quality information on social Q&A sites (e.g., best answers), relatively less attention has been paid to what affects users’ credibility assessments of information in the social Q&A context. The present study developed a social Q&A platform-specific framework for web credibility assessment, including 21 criteria under six types of web credibility, based on a literature analysis and case study of two online Q&A communities, Stack Exchange and Wikipedia Reference Desk. Using the selected sites’ policies and guidelines (n = 46) as the source of evidence, the case study revealed that content-related attributes (e.g., evidence-based, pertinence) were most frequently identified (12 of 21 criteria) as potential cues and heuristics for web credibility assessments of social Q&A sites, followed by author-related (five of 21; e.g., reputation) and design-related (four of 21; e.g., engaging design) factors. Design-related criteria were rarely included in previous models of web credibility on social Q&A or similar peer-knowledge production platforms. However, our findings showing that both Stack Exchange and Wikipedia Reference Desk have policies regarding all four design-related criteria in our framework—engaging design, moderation, design appropriateness, and ease of use—indicate the potential influences of design features on users’ web credibility assessment on social Q&A sites. Some differences emerged between the two cases, such as policies regarding the answerer's credentials or semantic accuracy that are present on Wikipedia Reference Desk but absent on Stack Exchange. Such differences in the sites’ policies reflect how they position themselves as social Q&A communities—Wikipedia, of which Wikipedia Reference Desk is a part, as an encyclopedia, and Stack Exchange as a community-based platform for learning, sharing knowledge, and building careers of users.  相似文献   

3.
【目的/意义】人们对知识付费的需求不断提升,但信息冗余和服务质量无法保证,会降低其付费意愿。本 文主要采用定性比较分析方法(fsQCA),探究社交网络平台中影响用户高知识付费意愿的联动组合因素。【方法/过 程】通过Python工具,获取知乎平台中职场、健康和法律领域的付费咨询版块中差异化用户的数据进行分析。【结 果/结论】研究表明,平台用户的高付费意愿是多个组合因素联动作用的结果,不同领域的用户付费意愿的影响因 素不同,部分因素可进行相互替代,知识付费平台应针对不同领域的用户采用不同的管理策略。【创新/局限】本文 从组态视角对社交网络平台中用户知识付费意愿联动效应进行了研究,但研究样本量有限,影响因素分析并没有 涵盖所有潜在因素,后续应补充完善。  相似文献   

4.
【目的/意义】探讨网络问答社区中意见领袖的社会与知识分享行为特征,为问答社区的发展提供改进建 议。【方法/过程】以知乎“旅行”问答话题下活跃用户为研究对象,通过python爬取用户的个人信息,利用数理统计 和社会网络分析对意见领袖的社会及知识分享行为特征展开研究。【结果/结论】研究发现,社会特征是意见领袖开 展知识共享活动的先决条件,网络问答社区的发展离不开社区用户的多元化;意见领袖为问答社区内容生成主力, 知识分享行为广泛分布于意见领袖的信息活动中且其行为影响力突出;中心团体联合促进意见领袖间的知识分 享,领袖群体间知识分享互动频繁。【创新/局限】对于意见领袖的特征分析只建立在“旅行”这一问答话题,样本数 量偏低,后期将会对更多的问答话题进行研究,以期得出更精准的、普适性更强的结论。  相似文献   

5.
【目的/意义】社会化问答社区目前已成为网络环境下用户搜寻和获取知识的重要途径。探析用户知识采 纳行为有助于提升社会化问答社区知识组织与服务能力,对社区的运营管理方面也具有重要的实践意义。【方法/ 过程】本文选取知乎作为研究对象,应用扎根理论方法,通过数据资料收集、三级编码等过程,结合认知心理学的相 关理论,构建了社会化问答社区用户知识采纳行为模型。【结果/结论】研究发现:自我认知、平台认知、社会认知三 个维度对用户知识采纳行为具有显著影响,并通过认知有用性、认知易用性两个中介变量和技术、情感因素两个调 节变量分别刺激用户知识采纳的意愿,从而影响知识采纳行为。【创新/局限】从认知视域基于扎根理论的方法探索 社会化问答社区知识采纳行为的影响因素模型,但采集的知乎的样本容量较小,概念模型的信度和效度并未经过 大样本检验。  相似文献   

6.
The purpose of the current study is to identify the user criteria and data-driven features, both textual and non-textual, for assessing the quality of answers posted on social questioning and answering sites (social Q&A) across four different knowledge domains—Science, Technology, Art and Recreation. A comprehensive review of literature on quality assessment of information produced in social contexts was carried out to develop the theoretical framework for the current study. A total of 23 user criteria and 24 data features were proposed and tested with high-quality answers obtained from four social Q&A sites in Stack Exchange. Findings indicate that content-related criteria and user and review features were the most frequently used in quality assessments, while the importance of user criteria and data features was variable across the knowledge domains. In the Technology Q&A site containing mostly self-help questions, the utility class was the most frequently used group of criteria. The popularity of the socio-emotional class was more apparent in discussion-oriented topic categories such as Art and Recreation, where people seek others’ opinions or advice. Users of Art and Recreation Q&A sites in Stack Exchange appear to place more value on answerers’ efforts and time, good attitudes or manners, personal experience, and the same taste. The importance of user features and the emphasis on answerer's expertise on the Science Q&A site was observed. Examining the connection or gap between user quality criteria and data features across the knowledge domains could help to better understand users’ evaluation behaviors for their preferred answers, and identify the potential of social Q&A for user education/intervention in answer quality evaluation. This examination also offers practical guidance for designing more effective social Q&A platforms, considering how to customize community support systems, motivate contributions, and control content quality.  相似文献   

7.
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   

8.
[目的/意义]旨在探索虚拟社区用户集体意愿研究。[方法/过程]结合在线问答社区特点,采用结构方程模型,先后利用SPSS 23.0和AMOS 21.0进行数据分析并进行模型验证。[结果/结论]研究认为,虚拟社区感、社会资本均对在线问答社区用户集体意愿产生正向影响;在线互动、线下互动除了直接对在线问答社区用户集体意愿产生正向影响,还可以通过虚拟社区感、社会资本对在线问答社区用户集体意愿产生间接的正向影响。  相似文献   

9.
【目的/意义】本文以虚拟学术社区用户为研究对象,探究其知识交流行为影响因素,为虚拟学术社区提升平台活跃度及用户知识交流效率提供建议。【方法/过程】文章在UTAUT模型的基础上,引入感知信任和激励两个变量,构建了虚拟学术社区用户知识交流影响因素模型,并通过问卷调查进行实证研究。【结果/结论】研究表明社会影响、感知信任和激励对用户知识交流意愿存在显著正向影响,绩效期望对用户知识交流意愿存在显著负向影响,努力期望、便利条件对于知识交流意愿的影响不显著。  相似文献   

10.
[目的/意义]社会化问答社区作为网络知识交互平台,其持续发展的关键在于促进用户知识共享,提升共享知识质量。[方法/过程]通过社区知识"质"与"量"的细分,将社区用户主动或被动参与社区知识共享获得的知识收益区分为"质"的收益与"量"的收益,并构建社会化问答社区用户知识共享的演化博弈模型,探讨不同博弈假设下问答社区知识共享的均衡状态。[结果/结论]通过仿真显示,社会化问答社区共享知识质量与用户共享行为策略会受到用户共享意愿与能力、用户认可与社区激励、感知共享成本等因素的影响。  相似文献   

11.
周涛  檀齐  邓胜利 《现代情报》2019,39(8):59-65
[目的/意义]近年来,知识付费作为一种新兴模式得到了快速发展。但由于内容质量参差不齐、用户感知收益不明确等问题,阻碍了用户的付费意愿,这不利于知识付费模式的持续发展。基于IS (信息系统)成功模型,研究了用户知识付费的影响因素。[方法/过程]研究共收集391份有效问卷,采用结构方程模型进行数据分析。[结果/结论]研究发现,平台的信息质量和服务质量对感知价值有显著影响,进而影响用户的付费意愿。研究结果启示知识付费平台应注重提高平台质量,严格把控内容质量,以促进用户付费意愿。  相似文献   

12.
Most social Q&A sites are designed to support solo searchers who access the aggregated opinions of other users, and ask and answer questions of their own. The purpose of this paper is to show how users in one social Q&A community defy system constraints to engage in brief, informal episodes of collaborative information seeking called microcollaborations. A brief literature review is presented, suggesting a view of information seeking as a combination of problem-centered information seeking, technological affordances and constraints, and social and affective factors. The results of content and transaction log analyses of user interactions suggest that topics of collaboration share a common threshold of complexity and invite responses containing both fact and opinion. Analysis also revealed that key elements in predicting a collaborative instance involve social capital and affective factors unrelated to the topic of the collaboration. Suggestions for supporting future lightweight microcollaborations, and implications for future research, are discussed.  相似文献   

13.
[目的/意义]从用户感知视角,探究学术虚拟社区知识共享的关键影响因素,有助于推动虚拟环境下的知识分享行为。[方法/过程]基于UTAUT模型,构建了一个包含绩效期望、努力期望、社会影响、便利条件和感知知识优势的综合效应模型,基于352份有效问卷,运用结构方程模型和回归分析进行了实证检验。[结果/结论]绩效期望、努力期望、社会影响正向影响知识共享意愿,并进而影响共享行为;便利条件正向影响知识共享行为;除自我身份与共享意愿之间的调节作用不显著外,感知知识优势调节各变量与知识共享意愿、共享行为之间的关系。提升知识分享的绩效预期和努力期望,增强社区成员的归属感、自我身份认同和自我效能感以及保持成员间适度的知识势差有助于提升虚拟社区知识共享行为。  相似文献   

14.
The purpose of this study is to explore the factors that prompt askers to switch from free to paid social question-and-answer (SQA) services. Prior studies have investigated users’ motivations and participation in free and paid SQA services; however, little attention has been paid to askers’ switching behavior. We empirically analyzed the content of qualitative interviews from 64 askers on a well-known SQA platform in China. Based on the push-pull-mooring framework, we identified and classified factors that influenced askers’ to switch from free to paid Q&A services, using the critical incident technique, after which we calculated the entropy weights of the 16 subcategories before and after the switch, using the entropy weight method. The findings suggest that askers’ switching behavior was influenced by push factors (i.e., dissatisfaction with the free SQA service), pull factors (i.e., satisfaction with the paid SQA service), and mooring factors (i.e., social factors, personal factors, situational factors). Moreover, the findings show that the effects of these factors vary significantly before and after a switch. Dissatisfaction with the quality of information from the free SQA service would influence users before a switch, whereas satisfaction with the quality of information from the paid SQA service would influence them after a switch. In terms of mooring factors, the effects of social and personal factors on askers’ switching behavior, especially subjective norms and cognitive lock-in, turn out to be less significant after a switch, whereas the effect of trust is more significant. Besides, the effects of situational factors are more or less the same before and after a switch. To the best of our knowledge, this paper is one of the first attempts to explore factors that affect askers’ switching behavior and to shed light on the managerial strategies of paid SQA services.  相似文献   

15.
吕美娇  李青青 《情报科学》2022,40(6):141-148
【目的/意义】解析社会化问答社区用户知识交互过程,识别用户交互过程中的关键影响因素,为管理者优 化用户体验,提高社区知识服务水平提供参考。【方法/过程】本文基于社会化问答社区信息生态链模型,利用问卷 调查法和访谈法,从交互主体、交互内容、交互平台以及交互环境四个维度构建了用户知识交互行为影响因素体 系,并运用DEMATEL方法对关键影响因素进行识别。【结果/结论】根据各因素的关联作用分析,表明了体验感知、 社区氛围、自我效能、价值认知、知识质量是社会化问答社区用户知识交互行为的关键影响因素,并据此为社区发 展提出了相关建议。【创新/局限】本文利用 DEMATEL 方法系统全面地分析了社会化问答社区知识交互行为影响 因素间的相互作用,揭示了影响用户知识交互行为的关键影响因素,为社区发展提出了相关建议。但研究数据存 在主观性,且缺乏实例验证。  相似文献   

16.
[目的/意义]在社会化问答社区,如何留住用户,促进用户的持续答题一直是人们关注的焦点。[方法/过程]根据社会交换理论,构建社区涉入、群体规范、效益导向快速关系、约束导向快速关系、问答满意度及持续答题意愿之间的影响关系模型,通过调查问卷收集数据,利用SPSS和AMOS进行统计分析和假设检验。[结果/结论]研究结果表明,效益导向快速关系和约束导向快速关系对问答满意度、持续答题意愿都有显著的正向影响,问答满意度在“快速关系→问答满意度→持续答题意愿”路径中起部分中介作用,社区涉入和群体规范能够促进效益导向与约束导向快速关系的建立。  相似文献   

17.
Private information disclosure on social networking sites (SNS) is one of the most important and active issues in the information management arena. The growing phenomenon of platforms requiring users to disclose personal information exposes the limitations of previous studies that only focus on users’ voluntary disclosure. In this study, we define two modes of users’ private information disclosure behavior: voluntary sharing and mandatory provision. Using the Communication Privacy Management theory, we built a framework to explain the impact of individual characteristics, context, motivation, and benefit–risk ratio on the user's willingness to disclose voluntarily or mandatorily. Our research shows that voluntary sharing is more likely to be driven by positive factors, such as perceived benefits, social network size, and personalization, while mandatory provision is affected by individual characteristics such as age, privacy policy, and perceived risks. One of our interesting findings is that perceived risk has less impact on voluntary sharing than previous studies suggested. When encouraging users to share information voluntarily, platforms do not need to pay as much attention to reducing perceived risk as in the mandatory providing mode, but should focus on improving perceived benefits. Being the first to classify and compare the private information disclosure modes of SNS users, our research enriches the existing literature and opens up new avenues for researchers and social networking platforms.  相似文献   

18.
[目的/意义]探索信息技术背景下用户量化自我持续参与意愿的影响因素及其作用机制,为提升用户的健康行为意愿提供合理的理论支撑.[方法/过程]基于用户感知视角,以技术接受模型为理论基础,运用问卷调查方法收集数据,利用SPSS软件和AMOS软件进行数据分析,建立了用户量化自我持续参与意愿影响因素模型.[结果/结论]感知有用性...  相似文献   

19.
Online healthcare communities (OHCs) have become producers of medical information. Solving the issue of how to effectively reuse such a large amount of medical data and discover its potential value is of the utmost importance for alleviating the shortage of medical resources. Online consultation has received widespread attention and population since its first appearance in 1999, and as a result, many diagnostic multi-turn questions and answers (Q&A) documents have become available. This type of document is formed by multiple rounds of patient questions and doctors’ diagnostic answers and contains massive medical knowledge and doctors’ diagnostic experience. Few studies concentrate on the modeling and recommendation of this type of document, yet making these documents convenient for reuse reduces the cost of medical consultation for patients and saves time addressing common diseases for doctors. In this paper, we focus on the modeling and understanding of diagnostic multi-turn Q&A records and propose a deep-learning recommendation framework based on patient medical information needs, the contents of Q&A records and doctor background information. With the evaluation based on a real dataset that contains pediatric consultation dialogues fetched from DingXiangYuan, a famous online consultation application in China, we found that the proposed model achieved a good performance on the recommendation of diagnostic multi-turn Q&A records and outperformed baseline models. In addition, we discussed a potential application scenario of the recommendation model, suggesting that the proposed model can promote the reduction of patient costs and doctors’ work pressure in countries or regions with insufficient medical resources.  相似文献   

20.
This study theorized and validated a model of knowledge sharing continuance in a special type of online community, the online question answering (Q&A) community, in which knowledge exchange is reflected mainly by asking and answering specific questions. We created a model that integrated knowledge sharing factors and knowledge self-efficacy into the expectation confirmation theory. The hypotheses derived from this model were empirically validated using an online survey conducted among users of a famous online Q&A community in China, “Yahoo! Answers China”. The results suggested that users’ intention to continue sharing knowledge (i.e., answering questions) was directly influenced by users’ ex-post feelings as consisting of two dimensions: satisfaction, and knowledge self-efficacy. Based on the obtained results, we also found that knowledge self-efficacy and confirmation mediated the relationship between benefits and satisfaction.  相似文献   

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