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.

We study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links arise in a variety of online settings; we study datasets from Epinions, Slashdot and Wikipedia. We find that the signs of links in the underlying social networks can be predicted with high accuracy, using models that generalize across this diverse range of sites. These models provide insight into some of the fundamental principles that drive the formation of signed links in networks, shedding light on theories of balance and status from social psychology; they also suggest social computing applications by which the attitude of one user toward another can be estimated from evidence provided by their relationships with other members of the surrounding social network.

Successful online communities have complex cooperative arrangements, articulations of work, and integration practices. They require technical infrastructure to support a broad division of labor. Yet the research literature lacks empirical studies that detail which types of work are valued by participants in an online community. A content analysis of Wikipedia barnstars – personalized tokens of appreciation given to participants – reveals a wide range of valued work extending far beyond simple editing to include social support, administrative actions, and types of articulation work. Our analysis develops a theoretical lens for understanding how wiki software supports the creation of articulations of work. We give implications of our results for communities engaged in large-scale collaborations.

Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the interplay between positive and negative relationships affects the structure of on-line social networks. We connect our analyses to theories of signed networks from social psychology. We find that the classical theory of structural balance tends to capture certain common patterns of interaction, but that it is also at odds with some of the fundamental phenomena we observe — particularly related to the evolving, directed nature of these on-line networks. We then develop an alternate theory of status that better explains the observed edge signs and provides insights into the underlying social mechanisms. Our work provides one of the first large-scale evaluations of theories of signed networks using on-line datasets, as well as providing a perspective for reasoning about social media sites. Author Keywords signed networks, structural balance, status theory, positive

How does “self-governance ” happen in Wikipedia? Through in-depth interviews with eleven individuals who have held a variety of responsibilities in the English Wikipedia, we obtained rich descriptions of how various forces produce and regulate social structures on the site. Our analysis describes Wikipedia as an organization with highly refined policies, norms, and a technological architecture that supports organizational ideals of consensus building and discussion. We describe how governance in the site is becoming increasingly decentralized as the community grows and how this is predicted by theories of commons-based governance developed in offline contexts. The trend of decentralization is noticeable with respect to both

Many online communities use tags – community selected words or phrases – to help people find what they desire. The quality of tags varies widely, from tags that capture a key dimension of an entity to those that are profane, useless, or unintelligible. Tagging systems must often select a subset of available tags to display to users due to limited screen space. Because users often spread tags they have seen, selecting good tags not only improves an individual’s view of tags, it also encourages them to create better tags in the future. We explore implicit (behavioral) and explicit (rating) mechanisms for determining tag quality. Based on 102,056 tag ratings and survey responses collected from 1,039 users over 100 days, we offer simple suggestions to designers of online communities to improve the quality of tags seen by their users.

Social media sites are often guided by a core group of committed users engaged in various forms of governance. A crucial aspect of this type of governance is deliberation, in which such a group reaches decisions on issues of importance to the site. Despite its crucial — though subtle — role in how a number of prominent social media sites function, there has been relatively little investigation of the deliberative aspects of social media governance. Here we explore this issue, investigating a particular deliberative process that is extensive, public, and recorded: the promotion of Wikipedia admins, which is determined by elections that engage committed members of the Wikipedia community. We find that the group decision-making at the heart of this process exhibits several fundamental forms of relative assessment. First we observe that the chance that a voter will support a candidate is strongly dependent on the relationship between characteristics of the voter and the candidate. Second we investigate how both individual voter decisions and overall election outcomes can be based on models that take into account the sequential, public nature of the voting.

With the growth in sociality and interaction around online news media, news sites are increasingly becoming places for communities to discuss and address common issues spurred by news articles. The quality of online news comments is of importance to news organizations that want to provide a valuable exchange of community ideas and maintain credibility within the community. In this work we examine the complex interplay between the needs and desires of news commenters with the functioning of different journalistic approaches toward managing comment quality. Drawing primarily on newsroom interviews and reader surveys, we characterize the comment discourse of SacBee.com, discuss the relationship of comment quality to both the consumption and production of news information, and provide a description of both readers ’ and writers’ motivations for usage of news comments. We also examine newsroom strategies for dealing with comment quality as well as explore tensions and opportunities for valuesensitive innovation within such online communities. Author Keywords Commenting systems, online journalism, online discourse

Online communities need regular maintenance activities such as moderation and data input, tasks that typically fall to community owners. Allowing all members to perform maintenance might make communities more robust and valuable. A key challenge in creating member-maintained communities is that we have little knowledge of how to design interfaces to motivate contributors. Social science theories of motivation may be helpful for making and evaluating design choices. We have used Karau and Williams ’ collective effort model to develop and evaluate designs that motivate members by making salient the unique contributions they could offer to a group. We also show that using oversight to check contributions to a community database of movies increases members ’ motivation to contribute and that peers can provide motivation as well as experts in this domain. Our experiments suggest a number of design elements and guidelines for increasing members ’ motivation to maintain their communities. The Problem Max is the movie czar, the de facto dictator of which movies get into the MovieLens recommender system. He’s the guardian of quality, the finder of movie facts, the defender of decency–the final authority on film. This suits Max well; he’s pleased with the quality of the movie database. Not all MovieLens users agree, however. Max is busy and adds movies slowly, and members sometimes disagree with his criteria for including movies. Useful information (DVD releases, MPAA ratings, etc.) is also not in the database. Max’s community is not unique—many groups have a Max. Most members ’ contributions to an online community pertain to what Preece calls its purpose (Preece 2000). Members post to discussion groups, rate movies, receive recommendations, and read each others ’ blogs. These contributions are visibly important and constitute the day to day business of the community. However, communities need inputs besides conversation, such as moderation, governance, and the maintenance of databases (i.e., members, movies, FAQs, and histories). These duties usually fall to the owners of the

Several years of consulting with online community hosts and managers have highlighted a variety of issues that recur across many online community development efforts. We summarize those issues in eight points that have functioned as useful guidelines to working with online communities, particularly within a corporate context. These recommendations focus on the location and purpose of the community, the monitoring of social activity within the space, the provision of feedback to participants and the organization and maintenance of the space. While this collection is particularly focused on issues relevant to community organizers closely involved in starting, maintaining or growing online communities, its principles are generally applicable for analyzing and understanding the dynamics within a variety of communities.