Trust,empathy, social identity,and contribution of knowledge within patient online communities

People are increasingly utilising patient online communities (POC) to seek useful health information and empathetic support. Success of POC is reliant upon the willingness of members to contribute useful information and knowledge. Few studies have examined the influence of interpersonal bonds between members on members’ contribution of information and knowledge within the context of POC. We investigated how trust, social identity, and empathy influence members’ willingness to contribute knowledge to POC. Results indicated that trust and social identity within POC positively influenced the development of empathy. Empathy in turn exerted a positive influence on willingness to contribute personal knowledge and experience. Social identity also directly influenced members’ willingness to contribute knowledge. The findings highlight the importance of trust, empathy, and a sense of group cohesiveness within online health settings in motivating members to contribute knowledge and support to other participants in POC.     

Perspectives on the evolution of online communities

The rapid growth of social networks opens interesting research opportunities to make use of the massive information exchanged in day-to-day communication. One of the active research issues related to this aspect is the study of online community formation and evolution in dynamic social networks. As community structure is usually ambiguous, then defining how it evolves over time becomes a challenge in terms of tracking mechanism and evaluation method. In this study, we review the online communities and their evolution tracking mechanisms and discuss the main categories of approaches for tracking community evolution and how they work. We analyse the different solutions proposed under each community evolution tracking category and provide an assessment of their projected performance. Finally, a discussion of analysis insights concerning community evolution and its influence is introduced.     

A comparison of empathic communication pattern for teenagers and older people in online support communities

This article reports a study that investigated the occurrences of empathy in online support communities for teenagers. Qualitative content analysis with 400 messages from a discussion board about depression was used to identify how empathy was expressed in the specific online communication. Emphasis was also placed on the comparison of this age group to older people, by comparing the results with those from a previous study on empathy in an online support community about depression for older people. Specifically, the analysis focused on the frequencies of the categories of the code scheme, linguistic characteristics of the communication content, the occurring components of empathy, and the roles as well as activities of the members. From our analysis, we concluded that young people exchanged a substantial amount of empathic emotional communication when participating in an online support community, and they communicated on a more personal level compared to older people, who tended to engage in a more formal communication. In addition, teenagers also showed a high level of understanding but lower level of concern compared to older persons when expressing empathy online.     

在线社交网络下基于信任度的消息传播模型

社交网络作为一种新兴的媒体具有广泛的社会影响力,且基于社交网络的营销方式逐渐成为一种新的发展趋势,因此研究社交网络中消息的传播具有重大的现实和经济意义。通过借鉴日常生活中人与人之间的信任原理,提出了一种基于信任度的消息传播模型。该模型首先利用个体的公开信息,使用数据挖掘的算法对个体进行分类;然后,根据同类和不同类个体之间的关系计算个体之间的信任度;最后,使用消息与个体的属性相似性以及信任度来计算消息可能传播范围。给出了相应的计算方法,并与两种基准方法对比,结果表明,该模型在准确度上提升15%左右,而所用时间降低50%以上。与数据集统计结果对比,该实验的结果与统计结果相差5%左右,充分表明该模型在实际应用中有比较好的效果。     

基于信誉推荐的网络购物主观信誉模型分析

针对网络购物中买卖双方的信任问题,建立了基于信誉推荐的主观信誉模型。该模型不仅引入了交易时间、交易金额及信誉推荐可信度等客观因素,还引入了第一印象等主观因素。基于Matlab的仿真实验表明,[Zi→j]模型能保证交易成功率的成功率在0.8以上,而且[Zi→j]模型比其他的信誉模型能更好地对抗恶意节点（特别是间歇性恶意节点）的恶意行为,具有较高的稳定性。     

网上拍卖中信任模型的研究综述

网上拍卖的匿名性以及不确定性是网上欺诈行为不断增加的重要客观因素,因此,建立一个完善的信任模型成为网上拍卖中亟待解决的问题。归纳了网上拍卖中受主、客观因素影响的信任概念模型,探讨了当今拍卖网站主要采用的信任模型以及存在的问题。列举了当前改进的信任计算模型,包括基于社会学理论的信任模型、基于统计的信任模型、基于概率的信任模型、基于不确定性理论的信任模型、基于语义的信任模型和基于网格的信任模型;在对上述模型的优势和不足进行具体分析的基础上,展望了未来信任模型的发展方向。     

Predicting continuance in online communities: model development and empirical test

Popular interest in online communities has grown rapidly in recent years as a result of the widespread diffusion of Web 2.0 applications. However, the full values and potential of online communities cannot be realised without users' ongoing participation. Thus, this study aims at developing and empirically testing a research model to examine users' continuance intention to participate in an online community based on an extended information systems (IS) continuance model. Specifically, entertainment value and affective commitment are included in the IS continuance model and empirically examined in the context of online communities. A total of 240 returns collected from an online survey, which was conducted among users of a website bulletin board-based community in China, were analysed using partial least squares. The results reveal that users' continuance intention to participate in an online community is determined by both satisfaction and affective commitment. Satisfaction and affective commitment are, in turn, influenced by positive disconfirmations of purposive and entertainment values. The findings of this study contribute not only to theory building in online community continuance but also inform online community moderators in their effort to develop strategies for retaining their users.     

选择在线交易服务者的多情境信任和声誉评估系统

在以信任和声誉值选择服务者的系统中,普遍存在的问题是在评估服务者的信任和声誉值时考虑因素过少,局限于系统内,以及方法缺少灵活性,导致选择的服务者不能满足用户多样性的要求。为了解决这个问题,提出一种应用于在线交易服务者选择的多情境信任和声誉评估系统,服务者通过注册的质量属性和担保资金获得信任和声誉启动值,由系统内、外的交易经历获得信任和声誉经验值,实际信任和声誉值由两者动态线性组合,后者所占比重随交易次数的增加而动态增加,根据用户设置的服务者的情境属性与实际信任和声誉值选择服务者。通过与其他方法对比测试,结果表明此方法更容易满足用户的各种要求。此信任和声誉评估系统不仅能给新服务者与其他服务者一个公平竞争的环境,也可以减少用户选中恶意服务者的机会。     

基于信任机制的无线传感器网络可靠传输路由协议

在无线传感器网络中,针对异常事件监测时会出现大量数据发送引起网络拥塞、数据包无法可靠传输的问题,提出一种基于信任机制的可靠传输路由协议(RTRPT)。该协议提出了梯度分簇模型以选取簇头节点。在无异常事件发生时,通过转发能量阈值找出传输数据的邻居节点,进行数据传输。同时对这些节点进行转发概率与历史信任度计算得到直接信任度,再通过这些节点交互间接评价得到间接信任度。将直接信任度、间接信任度、距离度量和剩余能量作为评价指标,量化后通过熵权法得到邻居节点的综合信任。在异常事件发生时,节点仅需选择综合信任度最大的邻居节点作为转发节点,建立路由路径。使用OMNeT++进行仿真验证,RTRPT与TSRP、ESRT相比,在传输大量数据包时节点丢包率分别降低69.4%、52.7%;节点传输延迟分别降低53.6%、34.8%;网络生命周期分别延长32.5%、15.7%。仿真结果表明,RTRPT能有效减少丢包、降低传输延迟、延长生命周期。     

The influence of familiarity,trust and norms of reciprocity on an experienced sense of community: an empirical analysis based on social online services

The growing use of social online services raises the question of what encourages members to participate actively and maintain accumulated social capital. Our research has particularly become aware of the relevance of familiarity, trust and reciprocity in understanding the members' sense of a virtual community (VC). Familiarity and trust are efficient criteria to assess and determine the extent to which one should engage in a virtual relationship. Furthermore, the effort of sharing experiences and knowledge must be based on the expectation of receiving certain returns. A structural equation modelling, specifically partial least squares, is proposed to assess the relationships between the constructs. Overall, the empirical results provided strong support for the hypotheses. Familiarity and trust lead the member to develop a growing perceived community support (PCS) and significantly influence the sense of a VC. Norms of reciprocity directly influence affective trust and PCS. Higher familiarity does not moderate the impact of affective trust on PCS, however. The results of this study could thus help social online service providers to create a successful business model and to determine the main drivers of the members' sense of a VC.     

Trust-based access control for collaborative systems

In distributed, heterogeneous and network-connected collaborative environments where resources are provided to diverse unknown users for their applications, it is necessary to define access control for resources. Access control for such systems is defined as the ability to authorise or repudiate access to resources by a particular user. Traditional access control solutions are inherently inadequate for collaborative systems because they are effective only in situations where the system knows in advance which users are going to access the resources and what are their access rights so that they can be predefined by the developers or security administrators, but in collaborative systems the number of users as well as their usage on resources is not static. Targeting collaborative systems, a fine grained, flexible, persistent trust-based model for protecting the access and usage of digital resources is defined in this paper using radial basis function neural network (RBFNN). RBFNN classifies the users requesting the resources as trustworthy and non-trustworthy based on their attributes. RBFNN is used for classification because of its ability to generalise well for even unseen data and non-iterative method employed in its training. A proof of concept implementation backed by extensive set of tests on the real data collected for one such collaborative systems, i.e. Enabling Grids for E-Science grid demonstrated that the design is sound for collaborative systems where access of resources are provided to large and unknown users with their variant set of requirements.     

Revealing only the superficial me: Exploring categorical self-disclosure online

Despite previous research demonstrating that online self-disclosure occurs in an accelerated manner compared to offline interactions, little is known about the content of online disclosures. This study highlights a number of issues that arise when exploring the self-disclosure of different types of personal information in initial general online communications. Forty-eight students and 48 non-students completed a purpose-developed attitude towards online relationship formation questionnaire and Magno’s (2009) self-disclosure for beliefs, relationships, personal matters, interests and intimate feelings questionnaire. Findings suggest that people are more likely to self-disclose information online the more positive is their attitude towards forming relationships online. Moreover, this self-disclosure initially occurs only for superficial self-information relating to personal matters and interests, implying that it is the quantity of online exchanges that is enhanced rather than the quality thereof. These findings raise a number of issues relating to type of self-information disclosed online, as well as intent, Internet arena, social identity, privacy, trust, and general methodological issues that would benefit from further experimental exploration. Implications of the findings for future research to explore categorical self-disclosure online within an existing theoretical framework of self-categorisation and self-identity theory as well as the self-memory-system model of autobiographical memory are discussed.     

面向在线社区用户的群体推荐算法研究

结合现有两种主要群体推荐算法的优势, 建立新的算法框架, 并引入差异度因素对模型进行优化。另外, 考虑到在线社区用户的特点, 定义互动度指标来描述群体成员间的互动程度, 通过分析其与推荐精度之间的关系, 探讨互动度对群体推荐的影响。选取豆瓣网数据进行实验, 并与传统方法进行比较, 结果表明, 融入差异度的算法具有更好的推荐效果, 且有效的互动机制能够保证较高的推荐精度。     

A dynamic bibliometric model for identifying online communities

Predictive modelling of online dynamic user-interaction recordings and community identification from such data becomes more and more important with the widespread use of online communication technologies. Despite of the time-dependent nature of the problem, existing approaches of community identification are based on static or fully observed network connections. Here we present a new, dynamic generative model for the inference of communities from a sequence of temporal events produced through online computer- mediated interactions. The distinctive feature of our approach is that it tries to model the process in a more realistic manner, including an account for possible random temporal delays between the intended connections. The inference of these delays from the data then forms an integral part of our state-clustering methodology, so that the most likely communities are found on the basis of the likely intended connections rather than just the observed ones. We derive a maximum likelihood estimation algorithm for the identification of our model, which turns out to be computationally efficient for the analysis of historical data and it scales linearly with the number of non-zero observed (L + 1)-grams, where L is the Markov memory length. In addition, we also derive an incremental version of the algorithm, which could be used for real-time analysis. Results obtained on both synthetic and real-world data sets demonstrate the approach is flexible and able to reveal novel and insightful structural aspects of online interactions. In particular, the analysis of a full day worth synchronous Internet relay chat participation sequence, reveals the formation of an extremely clear community structure.     

Determinants of success for online communities: an empirical study

Although online communities can significantly facilitate collaboration among Internet users, the determinants of success of online communities have seldom been studied empirically. Using the updated DeLone and McLean information systems success model as a theoretical framework, this study proposes a research model to examine the determinants for successful use of online communities. Based on a survey of 165 community members, this study uses structural equation modelling (SEM) approach to investigate the research model. The analytical results strongly support the appropriateness of the research model in identifying the determinants of success of online communities. The analytical results also showed that system quality, information quality and service quality had a significant effect on member loyalty through user satisfaction and behavioural intention to use the online community. Finally, this study discusses the implications of these findings and offer directions for future research.     

Determinants of success for online communities: an empirical study

Although online communities can significantly facilitate collaboration among Internet users, the determinants of success of online communities have seldom been studied empirically. Using the updated DeLone and McLean information systems success model as a theoretical framework, this study proposes a research model to examine the determinants for successful use of online communities. Based on a survey of 165 community members, this study uses structural equation modelling (SEM) approach to investigate the research model. The analytical results strongly support the appropriateness of the research model in identifying the determinants of success of online communities. The analytical results also showed that system quality, information quality and service quality had a significant effect on member loyalty through user satisfaction and behavioural intention to use the online community. Finally, this study discusses the implications of these findings and offer directions for future research.     

一种基于信任的Web Services动态访问控制模型

服务请求者身份的不可知性及其行为的动态不确定性,给Web Services的安全带来了严峻的挑战.在研究和分析现有信任模型不足的基础上,提出一种基于信任的Web Services动态访问控制模型（DWTBAC）.新模型引入时间权重、上下文和推荐强度等客观因素,改进信任值的计算方法,根据信任值-信任等级-权限强度的三元映射关系进行授权管理,实现部分授权.为了抵制恶意行为,提出一种基于服务质量惩罚机制的直接交互经验值更新算法.仿真结果表明,新的访问控制方式,很好地实现了实体信任值随其行为而改变的动态特性,能有效地遏制恶意用户的不良行为,满足Web Services访问控制的安全性和动态性需求.     

Trust and online information-sharing in close relationships: a cross-cultural perspective

Culture has an essential influence on online trust building in close relationships. The objective of this study was to investigate the effect of culture on interpersonal trust and online information-sharing in close relationships. A social dilemma game experiment was conducted by inviting close friend dyads from interdependent (that is, Chinese) or independent cultures (that is, German). Their trust and information-sharing performance in either online text chatting or face-to-face communication were examined. The results showed that in close relationships, Chinese participants had higher interpersonal trust and objective-sharing performance than German participants; Chinese trust and self-evaluated performance were not influenced by communication media; in comparison, German participants’ trust and self-evaluated performance significantly dropped online. The results confirmed that interdependent people are more relation-oriented in building their trust than independent people. Implications for online information-sharing management and the interface design were provided.     

Guidelines for facilitating the development of learning communities in online courses

Online learning has grown exponentially in recent years; however, dropout problem remains challenging for some online programmes. The dropout problem can be attributed to a number of reasons, with a lack of interaction between learners and the instructor constituting one of the main reasons. The lack of interaction also leads to learners' feeling of isolation. Learning communities can provide learners with an environment conducive to increased interactions and alleviate their feeling of isolation. Unfortunately, there are no clear rules that instructors can follow to help learners create learning communities. In this paper, we propose guidelines for online instructors to facilitate the development of learning communities in online courses. We first review the definition of a learning community, importance of a learning community and factors affecting the development of a learning community. Afterwards, based on a review of the existing guidelines and other relevant literature, we propose guidelines for facilitating the development of learning communities in online courses.     

Building professional holding environments for crowd work job crafting through online communities

Work is increasingly being organised via online platforms outside guiding organisational structures. Instead of having colleagues at work, crowd workers connect in online communities. We investigate how crowd workers build professional holding environments in online communities to compensate for the lack of organisational structures and we consider how they craft their crowd work activities to enhance their work experience and reduce its long-term precarity. Following a qualitative research design, this paper uses 675 forum interactions collected across six online communities. Based on our findings, we propose the concept of professional holding environments and provide a model for building such holding environments and job crafting in online communities. We thereby expand previous research on holding environments comprised of family members and friends by revealing the impact of professional online communities and their role in professionalisation and crafting supportive social structures in online crowd work.