Member-maintained communities ask their users to perform tasks the community needs. From Slashdot, to IMDb, to Wikipedia, groups with diverse interests create communitymaintained artifacts of lasting value (CALV) that support the group’s main purpose and provide value to others. Said communities don’t help members find work to do, or do so without regard to individual preferences, such as Slashdot assigning meta-moderation randomly. Yet social science theory suggests that reducing the cost and increasing the personal value of contribution would motivate members to participate more. We present SuggestBot, software that performs intelligent task routing (matching people with tasks) in Wikipedia. SuggestBot uses broadly applicable strategies of text analysis, collaborative filtering, and hyperlink following to recommend tasks. SuggestBot’s intelligent task routing increases the number of edits by roughly four times compared to suggesting random articles. Our contributions are: 1) demonstrating the value of intelligent task routing in a real deployment; 2) showing how to do intelligent task routing; and 3) sharing our experience of deploying a tool in Wikipedia, which offered both challenges and opportunities for research.

Online communities depend upon the commitment and voluntary participation of their members. Community design—site navigation, community structure and features, and organizational policies—is critical in this regard. Community design affects how people can interact, the information they receive about one another and the community, and how they can participate in community activities. We argue that the constraints and opportunities inherent in online community design influence how people become attached to the community and whether they are willing to expend effort on its behalf. We examine two theories of group attachment and link these theories with design decisions for online communities. Common identity theory makes predictions about the causes and consequences of people’s attachment to the group as a whole. Common bond theory makes predictions about the causes and consequences of people’s attachment to individual group members. We review causes of common identity and common bond, and show how they result in different kinds of attachment and group outcomes. We then show how design decisions, such as those focused on recruiting newcomers versus retaining existing members, constraining or promoting off-topic discussion, and limiting group size or allowing uncontrolled growth, can lead to common identity or interpersonal bonds among community members, and consequently to different levels and forms of community participation by those so motivated.

Many online communities are emerging that, like Wikipedia, bring people together to build community-maintained artifacts of lasting value (CALVs). Motivating people to contribute is a key problem because the quantity and quality of contributions ultimately determine a CALV’s value. We pose two related research questions: 1) How does intelligent task routing—matching people with work—affect the quantity of contributions? 2) How does reviewing contributions before accepting them affect the quality of contributions? A field experiment with 197 contributors shows that simple, intelligent task routing algorithms have large effects. We also model the effect of reviewing contributions on the value of CALVs. The model predicts, and experimental data shows, that value grows more slowly with review before acceptance. It also predicts, surprisingly, that a CALV will reach the same final value whether contributions are reviewed before or after they are made available to the community.

Abstract—The NameVoyager, a Web-based visualization of historical trends in baby naming, has proven remarkably popular. We describe design decisions behind the application and lessons learned in creating an application that makes do-it-yourself data mining popular. The prime lesson, it is hypothesized, is that an information visualization tool may be fruitfully viewed not as a tool but as part of an online social environment. In other words, to design a successful exploratory data analysis tool, one good strategy is to create a system that enables “social ” data analysis. We end by discussing the design of an extension of the NameVoyager to a more complex data set, in which the principles of social data analysis played a guiding role. Index Terms—Design study, time-varying data visualization, human-computer interaction, social data analysis. 1

Online communities need regular maintenance activities such as moderation and data input, tasks that typically fall to community owners. Communities that allow all members to participate in maintenance tasks have the potential to be more robust and valuable. A key challenge in creating member-maintained communities is building interfaces, algorithms, and social structures that encourage people to provide high-quality contributions. We use Karau and Williams ’ collective effort model to predict how peer and expert editorial oversight affect members ’ contributions to a movie recommendation website and test these predictions in a field experiment with 87 contributors. Oversight increased both the quantity and quality of contributions while reducing antisocial behavior, and peers were as effective at oversight as experts. We draw design guidelines and suggest avenues for future work from our results. Author Keywords online communities, participation, contribution, membermaintained,

Item-oriented Web sites maintain repositories of information about things such as books, games, or products. Many of these Web sites offer discussion forums. However, these forums are often disconnected from the rich data available in the item repositories. We describe a system, movie linking, that bridges a movie recommendation Web site and a movieoriented discussion forum. Through automatic detection and an interactive component, the system recognizes references to movies in the forum and adds recommendation data to the forums and conversation threads to movie pages. An eight week observational study shows that the system was able to identify movie references with precision of.93 and recall of.78. Though users reported that the feature was useful, their behavior indicates that the feature was more successful at enriching the interface than at integrating the system. Author Keywords online asynchronous discussion, user interface, recommender system

Many small online communities would benefit from increased diversity or activity in their membership. Some communities run the risk of dying out due to lack of participation. Others struggle to achieve the critical mass necessary for diverse and engaging conversation. But what tools are available to these communities to increase participation? Our goal in this research was to spark contributions to the movielens.org discussion forum, where only 2 % of the members write posts. We developed personalized invitations, messages designed to entice users to visit or contribute to the forum. In two field experiments, we ask (1) if personalized invitations increase activity in a discussion forum, (2) how the choice of algorithm for intelligently choosing content to emphasize in the invitation affects participation, and (3) how the suggestion made to the user affects their willingness to act. We find that invitations lead to increased participation, as measured by levels of reading and posting. More surprisingly, we find that invitations emphasizing the social nature of the discussion forum are effective, while invitations emphasizing non-social aspects of the discussion are less so. ACM Classification: H.4.3 Communications Applications:

We design a field experiment to explore the use of social comparison to increase contributions to an online community. We find that, after receiving behavioral information about the median user’s total number of movie ratings, users below the median demonstrate a 530-percent increase in the number of monthly movie ratings, while those above the median decrease their ratings by 62-percent. When given outcome information about the average user’s net benefit score, aboveaverage users mainly engage in activities that help others. Our findings suggest that effective personalized social information can increase the level of public goods provision. (JEL C93, H41) With the increasing popularity of the Internet, information technology is changing the way we interact, entertain, communicate and consume. In online communities, groups of people meet to share information, discuss mutual interests, play games and carry out business. Users of communities such as SourceForge

In this paper we present the design, implementation, and evaluation of Jiminy: a framework for explicitly rewarding users who participate in reputation management systems by submitting ratings.

Social navigation is a promising approach for supporting privacy and security management. By aggregating and presenting the choices made by others, social navigation systems can provide users with easily understandable guidance on security and privacy decisions, rather than requiring that they understand low-level technical details in order to make informed decisions. We have developed two prototype systems to explore how social navigation can help users manage their privacy and security. The Acumen system employs social navigation to address a common privacy activity, managing Internet cookies, and the Bonfire system uses social navigation to help users manage their personal firewall. Our experiences with Acumen and Bonfire suggest that, despite the promise of social navigation, there are significant challenges in applying these techniques to the domains of end-user privacy and security management. Due to features of these domains, individuals may misuse community data when making decisions, leading to incorrect individual decisions, inaccurate community data, and “herding ” behavior that is an example of what economists term an informational cascade. By understanding this phenomenon in these terms, we develop and present two general approaches for mitigating herding in social navigation systems that support end-user security and privacy management, mitigation via algorithms and mitigation via user interaction. Mitigation via user interaction is a novel and promising approach to mitigating cascades in social navigation systems. Categories and Subject Descriptors H5.3 [Information interfaces and presentation (e.g., HCI)]: Group and Organizational Interfaces- collaborative computing, theory and models. K4.1 [Computers and Society]: Public Policy Issues – privacy.