Robert E. Kraut

Using Social Psychology to Motivate Contributions to Online Communities

Under-contribution is a problem for many online communities. Social psychology theories of social loafing and goal-setting can lead to mid-level design goals to address this problem. We tested design principles derived from these theories in four field experiments involving members of an online movie recommender community. In each of the experiments participated were given different explanations for the value of their contributions. As predicted by theory, individuals contributed when they were reminded of their uniqueness and when they were given specific and challenging goals. However, other predictions were disconfirmed. For example, in one experiment, participants given group goals contributed more than those given individual goals. The article ends with suggestions and challenges for mining design implications from social science theories.

Social capital on facebook: differentiating uses and users

Though social network site use is often treated as a monolithic activity, in which all time is equally social and its impact the same for all users, we examine how Facebook affects social capital depending upon: (1) types of site activities, contrasting one-on-one communication, broadcasts to wider audiences, and passive consumption of social news, and (2) individual differences among users, including social communication skill and self-esteem. Longitudinal surveys matched to server logs from 415 Facebook users reveal that receiving messages from friends is associated with increases in bridging social capital, but that other uses are not. However, using the site to passively consume news assists those with lower social fluency draw value from their connections. The results inform site designers seeking to increase social connectedness and the value of those connections.

Predicting Continued Participation in Newsgroups

Turnover in online communities is very high, with most people who initially post a message to an online community never contributing again. In this paper, we test whether the responses that newcomers receive to their first posts influence the extent to which they continue to participate. The data come from initial posts made by 2,777 newcomers to six public newsgroups. We coded the content and valence of the initial post and its first response, if it received one, to see if these factors influenced newcomers’ likelihood of posting again. Approximately 61% of newcomers received a reply to their initial post, and those who got a reply were 12% more likely to post to the community again; their probability of posting again increased from 44% to 56%. They were more likely to receive a response if they asked a question or wrote a longer post. Surprisingly, the quality of the response they received—its emotional tone and whether it answered a newcomer’s question—did not influence the likelihood of the newcomer’s posting again.

Using social psychology to motivate contributions to online communities

Under-contribution is a problem for many online communities. Social psychology theories of social loafing and goal-setting can provide mid-level design principles to address this problem. We tested the design principles in two field experiments. In one, members of an online movie recommender community were reminded of the uniqueness of their contributions and the benefits that follow from them. In the second, they were given a range of individual or group goals for contribution. As predicted by theory, individuals contributed when they were reminded of their uniqueness and when they were given specific and challenging goals, but other predictions were not borne out. The paper ends with suggestions and challenges for mining social science theories as well as implications for design.

Motivating participation by displaying the value of contribution

One of the important challenges faced by designers of online communities is eliciting sufficent contributions from community members. Users in online communities may have difficulty either in finding opportunities to add value, or in understanding the value of their contributions to the community. Various social science theories suggest that showing users different perspectives on the value they add to the community will lead to differing amounts of contribution. The present study investigates a design augmentation for an existing community Web site that could benefit from additional contribution. The augmented interface includes individualized opportunities for contribution and an estimate of the value of each contribution to the community. The value is computed in one of four different ways: (1) value to self; (2) value to a small group the user has affinity with; (3) value to a small group the user does not have affinity with; and (4) value to the entire user community. The study compares the effectiveness of the different notions of value to 160 community members.

Mopping up: modeling wikipedia promotion decisions

This paper presents a model of the behavior of candidates for promotion to administrator status in Wikipedia. It uses a policy capture framework to highlight similarities and differences in the communitys stated criteria for promotion decisions to those criteria actually correlated with promotion success. As promotions are determined by the consensus of dozens of voters with conflicting opinions and unwritten expectations, the results highlight the degree to which consensus is truly reached. The model is fast and easily computable on the fly, and thus could be applied as a self-evaluation tool for editors considering becoming administrators, as a dashboard for voters to view a nominees relevant statistics, or as a tool to automatically search for likely future administrators. Implications for distributed consensus-building in online communities are discussed.

Socialization tactics in wikipedia and their effects

Socialization of newcomers is critical both for conventional groups. It helps groups perform effectively and the newcomers develop commitment. However, little empirical research has investigated the impact of specific socialization tactics on newcomers commitment to online groups. We examined WikiProjects, subgroups in Wikipedia organized around working on common topics or tasks. In study 1, we identified the seven socialization tactics used most frequently: invitations to join, welcome messages, requests to work on project-related tasks, offers of assistance, positive feedback on a new members work, constructive criticism, and personal-related comments. In study 2, we examined their impact on newcomers commitment to the project. Whereas most newcomers contributed fewer edits over time, the declines were slowed or reversed for those socialized with welcome messages, assistance, and constructive criticism. In contrast, invitations led to steeper declines in edits. These results suggest that different socialization tactics play different roles in socializing new members in online groups compared to offline ones.

Effectiveness of shared leadership in online communities

Traditional research on leadership in online communities has consistently focused on the small set of people occupying leadership roles. In this paper, we use a model of shared leadership, which posits that leadership behaviors come from members at all levels, not simply from people in high-level leadership positions. Although every member can exhibit some leadership behavior, different types of leadership behavior performed by different types of leaders may not be equally effective. This paper investigates how distinct types of leadership behaviors (transactional, aversive, directive and person-focused) and the legitimacy of the people who deliver them (people in formal leadership positions or not) influence the contributions that other participants make in the context of Wikipedia. After using propensity score matching to control for potential pre-existing differences among those who were and were not targets of leadership behaviors, we found that 1) leadership behaviors performed by members at all levels significantly influenced other members motivation; 2) transactional leadership and person-focused leadership were effective in motivating others to contribute more, whereas aversive leadership decreased other contributors motivations; and 3) legitimate leaders were in general more influential than regular peer leaders. We discuss the theoretical and practical implication of our work.

Talk amongst yourselves: inviting users to participate in online conversations

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 increase user activity, while invitations emphasizing other details of the discussion are less successful.

Identifying shared leadership in Wikipedia

In this paper, we introduce a method to measure shared leadership in Wikipedia as a step in developing a new model of online leadership. We show that editors with varying degrees of engagement and from peripheral as well as central roles all act like leaders, but that core and peripheral editors show different profiles of leadership behavior. Specifically, we developed machine learning models to automatically identify four types of leadership behaviors from 4 million messages sent between Wikipedia editors. We found strong evidence of shared leadership in Wikipedia, with editors in peripheral roles producing a large proportion of leadership behaviors.