Online Identity Crisis Identity Issues in Online Communities

Minds and Machines - How have online communities affected the ways their users construct, view, and define their identity? In this paper, we will approach this issue by considering two...     

在线身份窃取攻击

通过网络仿冒进行金融欺诈活动是当前的安全热点问题之一,越来越引起人们的重视。本文介绍了网络仿冒等在线身份窃取类攻击的有关情况和技术特点,并介绍了应对此类攻击的一些问题。     

Distributed Apprenticeship in Online Communities

Supporting learning in online communities is an important direction for the future of human–computer interaction as people increasingly leverage social technologies to support professional growth and development. However, few have studied how people leverage the socio-technical affordances of online informal workplace communities to develop professional skills in the absence of dedicated expert guidance. We draw from theories of apprenticeship to introduce an emergent theory of distributed apprenticeship, which outlines how community expectations of transparency and mutual support allow for instruction to be directed by a distributed network of nonexperts. We develop distributed apprenticeship through a qualitative study of crowdfunding entrepreneurs, where novices leverage social interactions with community members to develop a wide range of entrepreneurial skills. We then generalize distributed apprenticeship to other workplace contexts and provide design implications for online communities where people develop professional skills with minimal dedicated formal guidance.     

The Venn of Identity: Options and Issues in Federated Identity Management

Federated identity management lets users dynamically distribute identity information across security domains, increasing the portability of their digital identities. It also raises new architectural challenges and significant security and privacy issues.     

Electronic Communities in E-Business: Their Role and Issues

Electronic communities are social aggregations of critical masses of people on the Internet who engage in public discussions, interactions, and information exchanges with sufficient human feeling on matters of common interest to form webs of personal relationships. Many such e-communities are rapidly evolving on the Internet, some initiated, organized, and controlled by community members themselves, some organized and controlled by marketers, and some by third parties acting as intermediaries between members and other interest groups such as marketers and advertisers. In this paper, we explore the role of e-communities as intermediaries in exchange relationships among community members and between community members and other interest groups such as marketers and advertisers from an economic perspective. In particular, we focus on the types of interactions that take place among community members and between community members and other interest groups and examine the economic and social issues involved in maintaining a healthy community. Deriving parallels from extant research in financial intermediation and social exchange theory, we explore conditions and incentive mechanisms under which such communities could develop and add value on the Internet. We also draw upon limited empirical examples from the World Wide Web to provide support to our propositions.     

Becoming Friends in Online Brand Communities: Evidence From China

With the aid of information technology, consumers have increasingly engaged in social interaction in online brand communities. How can these strangers make friends online? Drawing on embeddedness theory and media richness theory, we examine the antecedents and intermediate mechanisms of online friendship. We theorize that online brand community interactivity aided by instant messaging technology is the main driving force of online friendship, whereas social presence and a sense of yuan (a Chinese concept describing predetermined relations) mediate online friendship development. Online friendship in turn enhances consumer online brand community commitment. We test our conceptual model with a sample of consumers from Chinese online sporting goods forums. The results support our hypotheses and inform online brand community research and practice.     

The Evolution of Online Identity

The author proposes that we must significantly improve how we authenticate ourselves on various computer systems to address growing security and privacy threats. As part of that process, we must adopt an identity metasystem that relies on in-person proofing and the passing of identity claims (such as claims about name, age, residency, or any other identity attribute). When people and organizations have the ability to transmit and consume such claims, they will be better able to engage safely in personal and commercial transactions.     

Identifying Seekers and Suppliers in Social Media Communities to Support Crisis Coordination

Effective crisis management has long relied on both the formal and informal response communities. Social media platforms such as Twitter increase the participation of the informal response community in crisis response. Yet, challenges remain in realizing the formal and informal response communities as a cooperative work system. We demonstrate a supportive technology that recognizes the existing capabilities of the informal response community to identify needs (seeker behavior) and provide resources (supplier behavior), using their own terminology. To facilitate awareness and the articulation of work in the formal response community, we present a technology that can bridge the differences in terminology and understanding of the task between the formal and informal response communities. This technology includes our previous work using domain-independent features of conversation to identify indications of coordination within the informal response community. In addition, it includes a domain-dependent analysis of message content (drawing from the ontology of the formal response community and patterns of language usage concerning the transfer of property) to annotate social media messages. The resulting repository of annotated messages is accessible through our social media analysis tool, Twitris. It allows recipients in the formal response community to sort on resource needs and availability along various dimensions including geography and time. Thus, computation indexes the original social media content and enables complex querying to identify contents, players, and locations. Evaluation of the computed annotations for seeker-supplier behavior with human judgment shows fair to moderate agreement. In addition to the potential benefits to the formal emergency response community regarding awareness of the observations and activities of the informal response community, the analysis serves as a point of reference for evaluating more computationally intensive efforts and characterizing the patterns of language behavior during a crisis.     

From Publics to Communities: Researching the Path of Shared Issues Through ICT

In recent years, citizens’ movements such as the Arab Spring or Euromaidan protests have clearly shown that, whenever affected – whether negatively or positively – by the state and government decisions, citizens act to deal with the shared issues. Groups of people who organize themselves to address (mainly political) issues were defined as a ‘public’ by the philosopher John Dewey. He believed it is necessary to improve communication to create a ‘Great Community’ as a cohesive group of a public. Although information and communication technologies (ICT) lead to ambivalent effects on pursuing this goal and often distract the mass of people from discussing these issues, we argue that nowadays ICT can improve communication and has the potential to foster the detection of issues and therefore promote the (trans-)formation of a public into an issue-based community. As our foundation we took a literature study covering the formation of publics and their potential to evolve into communities, as well as their interplay with technology. This formed the basis for the development of our operational model that ‘follows the issues’ for capturing the (trans-)formation of a public. Based on our model, we outline different perspectives on detecting shared issues as early indicators for publics based on ICT and derive implications for researching this process from a practical perspective.     

A Practice‐Based Approach to Understanding Participation in Online Communities

The take up of online communities in organisations is often patchy. Previous studies, mainly within the cognitive tradition of thinking, explain such non‐participation either through features of technology or through individuals' motivational structures, and look at participation as a static, individualistic and functionalistic phenomenon. The aim of this article is to explore the insights on participation from a practice‐based approach (PBA). The paper draws upon empirical data from the use of collaborative technology in a Mexican University. The adoption of community technology is shown to be shaped by dynamic, collective, historical and contextual forces. Based on these findings, the value and the limits of the PBA, and a series of contributions and practical implications are discussed.     

在线教育环境中学习共同体研究综述

随着信息技术与教育的深度融合,蓬勃发展的在线教育已成为教育信息化进程的新常态,并产生了海量的教育数据,但也面临辍学率高、课程完成率低、监管不足等问题,因此如何对海量教育数据进行挖掘和分析是解决这些问题的关键.学习共同体是以学习者为核心要素的学习组织,强调学习过程中学习者之间互动交流、资源共享以及协作学习等行为,从而完成共同的学习任务或目标.对在线教育环境中学习共同体的研究进行回顾、分析和展望.首先,介绍在线教育环境中学习共同体的背景与重要性.其次,介绍不同学科中学习共同体的定义.然后,总结同质、异质和混合3种类型学习共同体的构建方法.接着,从共享、协作和激励3个方面讨论学习共同体的管理机制.最后,探讨和展望学习共同体未来的研究方向.     

在线身份信息泄露及一种解决方案

本文在分析在线身份泄露的原因的基础上,提出了一种新型身份认证协议及其系统方案。首先,通过引入一个自主的智能输入设备,令所有用户信息的输入与变换处理均在该设备上封闭性完成,从而保证用户输入的原始账号与口令等信息不会泄露;其次,以用户欲访问网站提供的秘密数据为参数,对用户的原始账号与口令进行变换处理,得到因网站秘密数据而异的用户注册或登录该网站的提交账号与口令。这样,即使注册到某个网站的账号口令泄露,也不会影响到到其它网站的身份信息安全;同时用户再无须为了安全而记忆大量账号与口令。最后再将提交账号与口令进行不低于服务安全要求的加密后上传到服务器。运用本方案,可望很大程度上解决在线身份信息泄露问题。     

Trust Prediction in Online Communities Employing Neurofuzzy Approach

Exploiting the opportunities provided by Web 2.0 technologies has led to the appearance of social web applications, which allow users to interact and collaborate with each other, thereby sharing experience in an online environment. Establishing a trust mechanism is vital in order to identify the trustful sources of information on the social web. Trust prediction can be a useful tool for identifying the potential trust relationships among users in an online community. Thereby, reliable participants can be recommended to users; this increases social interaction among users and makes the trust network denser. The main contribution of this study is to investigate the effectiveness of soft computing and neurofuzzy techniques within the context of trust prediction. Therefore, an adaptive neurofuzzy inference system (ANFIS) as a representative of neurofuzzy techniques is compared with the widely used classification techniques including C4.5 decision tree, artificial neural network (ANN), logistic regression, and Bayesian network. All methods are applied on a portion of data obtained from the Epinions network. The results of empirical experiments indicate that ANFIS achieves the best performance in terms of area under ROC (AUC) among all other methods. Furthermore, ANFIS follows closely a C4.5 algorithm concerning F-measure. Overall, the results of experiments indicate that AFNIS can be a suitable candidate for prediction of unknown trust relationships in an online community.     

Empowerment Strategies for Ideation through Online Communities

Successful ideation is vital for new product development. In a novel approach, firms have recently and successfully empowered their customers through online communities by applying democratic principles to open innovation. In this paper, we borrow insights from the democratic system to examine the enhancement of, and the boundary conditions for, the adoption of this empowerment strategy. We conducted three series of experiments to investigate whether online community size and lead user status might affect the link between empowerment strategy and perceived impact. This study also highlights the double‐edged influence of the selected outcome of an empowerment task by focusing on the negative emotions that threaten the effectiveness and sustainability of empowerment strategy. Our results show that empowerment strategy in small communities and higher lead user status can produce higher perceived impact. In addition, the outcome of empowerment strategy may engender positive and negative emotions in members of the community, which leads to distinct and different corresponding behaviour. The theoretical and practical implications of our research are discussed in the conclusion.     

基于结构稳定性校准的在线式社区识别

本文探讨在线社会网络的社区识别问题, 重点研究网络演变特性对社区结构产生的影响. 首先基于节点的邻域倾向性提出社区稳定性的概念并给出稳定社区的快速识别算法, 然后设计了一种基于事件的社区稳定性校准算法以此识别新网络的社区结构. 由于算法的局部搜索策略, 该方法无需在新时间片段重复执行, 并且可以在无参数条件下识别加权网络中具有任意形状的社区结构. 在人工合成网络和真实网络上的实验结果验证了算法的可行性和有效性.     

Ritual in Online Communities: A Study of Post-Voting in MOOC Discussion Forums

When building a community, whether online or offline, rituals are key. They guide social interaction by expressing standards of behavior and social boundaries through patterned series of symbolic words and acts. With Massive Open Online Courses (MOOCs) as a case study, this article demonstrates how post-voting in online discussion forums—including those in education contexts—can both enforce and undermine the development of community precisely because of the ritual power such mechanisms assume, inclusive and exclusive. Anyone seeking to cultivate communities online through the use of discussion forums should be wary of this issue with regard to user interaction.     

在线技术社区的用户技能与兴趣发现

在线技术社区是技术爱好者或者从业者进行技术交流、咨询和分享的重要平台。社区运营者如果能够准确掌握每个用户的技能和兴趣,对用户进行画像,将有助于为用户提供精准的推荐和个性化服务,从而增加用户的黏性和社区的活跃度。考虑到社区用户既是内容的生产者(作者)又是内容的消费者(读者),生产者体现用户技能,消费者体现用户兴趣,从而提出了一种作者—读者—话题(author-reader-topic,ART)模型,同时对用户的技能和兴趣进行建模。该模型可以将文档的作者和读者关联起来,因而能够提升话题的聚集效果,产生更准确的作者话题分布和读者话题分布。该文基于CSDN技术社区的真实数据集进行了实验对比和分析,实验结果表明,该文提出的ART模型能够有效地发现用户的技能和兴趣,明显优于现有的各种话题模型。     

一种融合话题和行为的在线问答社区领域专家发现方法

根据在线问答社区中答案的产生过程,提出一种“问题-回答者-话题”(Question-Answerer-Topic, QAT)模型,对“问题-回答者对”(question-answerer pair)的领域话题分布进行建模,并结合社区中的点赞行为,融入用户在每个问题下答案的获赞数据,计算用户在领域话题分布下的专业水平,最后结合链接分析的方法,提出一种主题敏感的PageRank改进模型,最终得到每位用户在领域话题下的专家得分。基于中文在线问答社区知乎网的人工智能领域真实数据集进行实验和对比分析,实验结果表明,本文提出的领域专家发现方法明显优于其他现有方法。     

在线社交网络社区的启发式挖掘框架

指出基于全局优化的社区挖掘方法的不足,给出OSNs网络及其社区挖掘的形式定义,提出一个启发式社区挖掘框架,在此框架下对包括LWP,Clauset,Schaeffer,Papadopoulos,Bagrow与Chen在内的6种启发式社区挖掘算法进行分析比较.通过3个真实OSNs网络的实验比较,验证了启发式社区挖掘框架的可行性,在结果社区有效性与时间效率上对6种启发式算法进行比较,实验结论为网络社区挖掘的工程实践与理论研究提供了借鉴.