The ties that bind: Social network principles in online communities

In a Web 2.0 environment, the online community is fundamental to the business model, and participants in the online community are often motivated and rewarded by abstract concepts of social capital. How networks of relationships in online communities are structured has important implications for how social capital may be generated, which is critical to both attract and govern the necessary user base to sustain the site. We examine a popular website, Slashdot, which uses a system by which users can declare relationships with other users, and also has an embedded reputation system to rank users called ‘Karma’. We test the relationship between user's Karma level and the social network structure, measured by structural holes, to evaluate the brokerage and closure theories of social capital development. We find that Slashdot users develop deep networks at lower levels of participation indicating value from closure and that participation intensity helps increase the returns. We conclude with some comments on mechanism design which would exploit these findings to optimize the social networks and potentially increase the opportunities for monetization.     

Administrator-users contribute more to online communities

Lack of user participation and contribution has been a long-standing problem for online communities. We proposed and examined new strategies for cultivating opinion leadership and enabling users to post articles outside of the community theme. We used social role theory to propose that online communities should encourage highly committed users to take administrator roles, which will increase their opinion leadership and contributions to both public spaces and their own user-controlled spaces. We collected multiple-wave and multiple-source data from 1,115 users of a large online community. The results indicate that encouraging users to take administrator roles increases their community contributions.     

Motivating participation in social computing applications: a user modeling perspective

The explosive growth of Web-based social applications over the last 10?years has led people to engage in online communities for various purposes: to work, learn, play, share time and mementos with friends and family and engage in public action. Social Computing Applications (SCA) allow users to discuss various topics in online forums, share their thoughts in blogs, share photos, videos, bookmarks, and connect with friends through social networks. Yet, the design of successful social applications that attract and sustain active contribution by their users still remains more of an art than a science. My research over the last 10?years has been based on the hypothesis that it is possible to incorporate mechanisms and tools in the design of the social application that can motivate users to participate, and more generally, to change their behavior in a desirable way, which is beneficial for the community. Since different people are motivated by different things, it can be expected that personalizing the incentives and the way the rewards are presented to the individual, would be beneficial. Also since communities have different needs in different phases of their existence, it is necessary to model the changing needs of communities and adapt the incentive mechanisms accordingly, to attract the kind of contributions that are beneficial. Therefore User and Group (Community) Modeling is an important area in the design of incentive mechanisms. This paper presents an overview of different approaches to motivate users to participate. These approaches are based on various theories from the area of social psychology and behavioral economics and involve rewards mechanisms, reputation, open group user modeling, and social visualization. Future trends are outlined towards convergence with the areas of persuasive systems design, adaptive/personalized systems, and intelligent social learning environments.     

Latent Users in an Online User-Generated Content Community

Online communities depend on the persistent contributions of heterogeneous users with diverse motivations and ways of participating. As these online communities exist over time, it is possible that users change the way in which they contribute to the site. Through interviews with 31 long-term members of a user-generated content community who have decreased their participation on the site, we examined the meaning that these users gave to their contribution and how their new participation patterns related to their initial motivations. We complement the reader-to-leader framework (Preece and Shneiderman: AIS Transactions on Human-Computer Interaction, vol. 1, no. 1, pp. 13–32, 2009) by propounding the concept of latent user to understand decreasing content contribution and user life-cycles in online communities. We showed that even though latent users decrease their content contribution, their participation becomes more selective and remained consistent with initial motivations to participate.     

User incentive mechanism in blockchain-based online community: An empirical study of steemit

The rise of blockchain technology has brought innovations in various business domains and spawned a new form of organization—the decentralized autonomous organization (DAO). Steemit is recognized as one of the earliest blockchain-based online communities, and a typical example of DAO. By endowing community members with new roles, the decentralization of blockchain-based communities brings changes to the design of user incentive mechanisms. However, few studies have paid attention to the user incentive mechanism when users play the dual roles of social participant and community owner. On the basis of social capital theory and psychological ownership theory, this study explores Steemit's incentive mechanism by evaluating the impact of these dual roles on user active participation behavior. The study adopts a two-way fixed effect negative binomial regression to test the research model. The results show that users’ social capital, share capital, social feedback, and economic feedback positively affect their active participation behavior. At the same time, social feedback and economic feedback play moderating roles on the effects of the dual capitals. Overall, this research provides both theoretical insights and practical implications for understanding, designing, and governing blockchain-based online communities.     

A semantic social network-based expert recommender system

This research work presents a framework to build a hybrid expert recommendation system that integrates the characteristics of content-based recommendation algorithms into a social network-based collaborative filtering system. The proposed method aims at improving the accuracy of recommendation prediction by considering the social aspect of experts’ behaviors. For this purpose, content-based profiles of experts are first constructed by crawling online resources. A semantic kernel is built by using the background knowledge derived from Wikipedia repository. The semantic kernel is employed to enrich the experts’ profiles. Experts’ social communities are detected by applying the social network analysis and using factors such as experience, background, knowledge level, and personal preferences. By this way, hidden social relationships can be discovered among individuals. Identifying communities is used for determining a particular member’s value according to the general pattern behavior of the community that the individual belongs to. Representative members of a community are then identified using the eigenvector centrality measure. Finally, a recommendation is made to relate an information item, for which a user is seeking an expert, to the representatives of the most relevant community. Such a semantic social network-based expert recommendation system can provide benefits to both experts and users if one looks at the recommendation from two perspectives. From the user’s perspective, she/he is provided with a group of experts who can help the user with her/his information needs. From the expert’s perspective she/he has been assigned to work on relevant information items that fall under her/his expertise and interests.     

Community Participation in Health Informatics in Africa: An Experiment in Tripartite Partnership in Ile-Ife, Nigeria

Participatory Design has mainly been practiced in Europe and North America. Our seven-year experience in Nigeria suggests that user participation is also a must in developing countries. However, the scope of participation needs to be expanded. For instance, in health informatics the communities served by the health facility in question need to be involved along with computer professionals and health providers. This paper presents the results of an experiment in tripartite partnership in systems design for Primary Health Care by designers, users/providers, and community representatives in Ile-Ife, Nigeria. The experience was extremely encouraging.     

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.     

Understanding lurkers in online communities: A literature review

In internet culture, lurkers are a special group of website users who regularly login to online communities but seldom post. This study aims to provide an overall understanding of lurkers by explaining the definition of lurkers, discussing the reasons for lurking and providing suggestions on de-lurking. To understand the reason for lurking, this study first explains why people participate in online communities by building an integrated model of motivational factors of online behaviors. This model classifies motivational factors into four categories: the nature of the online community, individual characteristics, the degree of commitment and quality requirement. Based on this model, four types of lurking reasons are identified: environmental influence, personal preference, individual-group relationship and security consideration. Finally, several strategies for motivating participation in online communities are provided, including external stimuli, improved user-friendliness, encouragement of participation and guidance for newcomers.     

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。     

Psychological empowerment and user satisfaction: Investigating the influences of online brand community participation

The exponential growth of online brand communities has created a platform where empowered consumers can share knowledge and experiences and participate in community activities. Drawing from psychological empowerment theory, this study proposes a comprehensive framework integrating both social and functional views to investigate the determinants that enhance psychological empowerment and user satisfaction, which consequently influence online brand community participation. By shedding light on the explanatory path routes and highlighting the underexplored and distinctive role of psychological empowerment, this study provides theoretical contributions to illustrate how an enabling environment can be cultivated to drive consumer participation in brand value co-creation.     

User Roles in Online Communities and Their Moderating Effect on Online Community Usage Intention: An Integrated Approach

Recently, it has been evident that the analysis of user data and content in online environments allows practitioners to understand how to motivate online community members and keep them frequently involved in the community, and so to manage these communities successfully. In this sense, practitioners should comprehend community members’ usage intentions to give a better service and to motivate them. However, different user types engage in such communities, so understanding their diverse needs is also essential for practitioners. In parallel, this article addresses the problem of the different user types existing in online communities, and each of them requires different strategies to be motivated and involved in the community. Thus, unlike previous studies, this study firstly identifies user roles in an online community based on the structural role theory, social network analysis, and community members’ contribution behavior. After that, it investigates members’ usage intentions based on the technology acceptance model and examines the moderating effect of identified user roles on their usage intentions. The study also guides practitioners to develop motivational strategies to keep each type of member continually satisfied.     

Understanding user motivation for evaluating online content: a self-determination theory perspective

In a digital society, people have access to all kinds of electronic information as online users. They have also contributed various content for exchanging ideas in the online community, which has not only extended the traditional knowledge sharing channels, but has also led to concerns about content quality and reliability. The literature suggests that user involvement in collaboratively evaluating the quality of online content for an online community is likely to be an effective means to ease these concerns. However, the understanding of users' intentions to be willing to take part in evaluating online content is still limited. Based on self-determination theory, this study proposes a research model to understand the extrinsic motivation of the user intention. The research model was tested using data collected from 303 participants who were recruited from online communities. The results show that three types of extrinsic motivation, namely identified motivation, introjected motivation, and external motivation, play an important role in user intention of collaboratively evaluating online content. In addition, the research findings suggest that user satisfaction of the three basic psychological needs of autonomy, competence, and relatedness influences different types of extrinsic motivation.     

Assessing flow experience in social networking site based brand communities

The sustenance of the Social Networking Site (SNS)-based brand communities relies on user retention and their active participation. Therefore, understanding the intrinsic aspects of user behavior in such communities is important for devising strategies to ensure user retention and active participation. Especially, information about the elements that induce flow experiences—the intrinsically enjoyable and immersive experiences—of users in SNS has become important for organizations that host online communities. In our empirical study, we chose to focus especially on SNS-based brand communities, as they are increasingly interesting from an organization-community interaction perspective, but they lack the instruments needed for measuring user experience. The present study addresses this gap by developing an instrument aimed at measuring the user’s flow experience on SNS-based brand communities. A cross-sectional survey with 577 Facebook brand community users was carried out. The findings show that enjoyment, concentration, and social interaction are the components that constitute a user’s flow experience. In addition to providing a valuable tool for business practitioners, the developed instrument offers several theoretical and practical implications for improving user experience of social media.     

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.     

Sustaining a Community Computing Infrastructure for Online Teacher Professional Development: A Case Study of Designing Tapped In

Community computing has recently grown to become a major research area in human–computer interaction. One of the objectives of community computing is to support computer supported cooperative work among distributed collaborators working toward shared professional goals in online communities of practice. A core issue in designing and developing community computing infrastructures – the underlying socio-technical layer that supports communitarian activities – is sustainability. Many community computing initiatives fail because the underlying infrastructure does not meet end user requirements; the community is unable to maintain a critical mass of users consistently over time; it generates insufficient social capital to support significant contributions by members of the community; or, as typically happens with funded initiatives, financial and human capital resource become unavailable to further maintain the infrastructure. Based on more than nine years of design experience with Tapped In – an online community of practice for education professionals – we present a case study that discusses four design interventions that have sustained the Tapped In infrastructure and its community to date. These interventions represent broader design strategies for developing online environments for professional communities of practice.     

Mediating roles of self-presentation desire in online game community commitment and trust behavior of Massive Multiplayer Online Role-Playing Games

Massive Multiplayer Online Role-Playing Games (MMORPGs), which allow simultaneous participation of several gamers, have attracted a great deal of attention recently. Since MMORPGs can be categorized as a type of online community, the behavior of MMORPGs users needs to be considered as the general behavior in online communities. However, previous studies of online communities did not pay enough attention to MMORPGs, in which users can express themselves by interacting actively through games and game avatars. Understanding the characteristics of MMORPGs as online game communities where users communicate and interact will allow games to be vitalized and users to be immersed in games in a more positive way. Hence, using self-presentation theory and social identity theory, this study examined the factors influencing self-presentation desire and the mediating role of self-presentation desire examined in terms of trust of and commitments to online game communities. The results showed that the interactivity in the spaces of MMORPGs had the biggest impacts on self-presentation desire; personal innovativeness and game design quality also was influential. The results also indicated that self-presentation desire caused trust of online games and eventually led to even stronger commitments to gamers.     

移动群智感知中面向任务需求的用户选择激励机制

现有的移动群智感知激励机制大多以平台为中心或是以用户为中心进行设计，缺乏对感知任务需求的多维考虑，从而无法切实地以任务为中心进行用户选择，导致无法满足任务需求的最大化和多样化。针对上述问题，提出一种面向任务需求的用户选择激励机制TRIM，这是一种以任务为中心的设计方法。首先，感知平台根据任务需求发布感知任务，并从任务类型、时空特性以及感知报酬等多维度构建任务向量以最大化满足任务需求，而感知用户则基于意愿偏好、个人贡献值以及期望报酬等属性构建用户向量，实现个性化选择感知任务参与响应；然后，通过引入高效且隐私保护的余弦相似度计算协议（PCSC），计算任务和用户的相似度并根据相似度高低进行用户匹配筛选得到目标用户集，更好地满足感知任务需求的同时保护用户隐私不泄露；最后，通过仿真实验表明，在感知任务和感知用户的匹配过程中，与采用Paillier加密协议的激励机制相比，TRIM缩短了指数级增量的计算时间开销，提高了计算效率；与采用直接余弦相似度计算协议的激励机制相比，TRIM保证了感知用户的隐私安全，达到了98%的匹配精确度。     

Community-organizing agent: An artificial intelligent system for building learning communities among large numbers of learners

Web-based (or online) learning provides an unprecedented flexibility and convenience to both learners and instructors. However, large online classes relying on instructor-centered presentations could tend to isolate many learners. The size of these classes and the wide dispersion of the learners make it challenging for instructors to interact with individual learners or to facilitate learner collaborations. Since extensive literature has confirmed that the substantial impact of learner interaction on learning outcomes, it is pedagogically critical to help distributed learners engage in community-based collaborative learning and to help individual learners improve their self-regulation. The E-learning lab of Shanghai Jiaotong University created an artificial intelligence system to help guide learners with similar interests into reasonably sized learning communities. The system uses a multi-agent mechanism to organize and reorganize supportive communities based on learners’ learning interests, experiences, and behaviors. Through effective award and exchange algorithms, learners with similar interests and experiences will form a community to support each others’ learning. Simulated experimental results indicate that these algorithms can improve the speed and efficiency in identifying and grouping homogeneous learners. Here, we will describe this system in detail and present its mechanism for organizing learning communities. We will conduct human experimentations in the near future to further perfect the system.