Socialization in online communities allows existing members to welcome and recruit newcomers, introduce them to community norms and practices, and sustain their early participation. However, socializing newcomers does not come for free: in large communities, socialization can result in a significant workload for mentors and is hard to scale. In this study we present results from an experiment that measured the effect of a lightweight socialization tool on the activity and retention of newly registered users attempting to edit for the first time Wikipedia. Wikipedia is struggling with the retention of newcomers and our results indicate that a mechanism to elicit lightweight feedback and to provide early mentoring to newcomers improves their chances of becoming long-term contributors.
A large literature has studied incentives and drivers of participation in online communities, with a focus on early socialization. Early research on Wikipedia and open source software projects suggests that a mix of intrinsic motivation and extrinsic rewards drives participation @cite_25 @cite_32 @cite_8 . Top contributors may have strong intrinsic motives to participate @cite_37 . Non-monetary rewards such as acknowledgements @cite_24 @cite_30 @cite_19 @cite_29 , badges @cite_6 @cite_7 , and gamified feedback @cite_15 have been shown to increase engagement of users. Certain forms of reward can exert fine-grained control, even though instilling long-term behavior still proves to be difficult @cite_35 .
@cite_30 @cite_35 @cite_37 @cite_7 @cite_8 @cite_29 @cite_32 @cite_6 @cite_24 @cite_19 @cite_15 @cite_25
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Gamification is growing increasingly prevalent as a means to incentivize user engagement of social media sites that rely on user contributions. Badges, or equivalent rewards, such as top-contributor lists that are used to recognize a user's contributions on a site, clearly appear to be valued by users who actively pursue and compete for them. However, different sites use different badge designs, varying how, and for what, badges are awarded. Some sites, such as StackOverflow, award badges for meeting fixed levels of contribution. Other sites, such as Amazon and Y! Answers, reward users for being among some top set of contributors on the site, corresponding to a competitive standard of performance. Given that users value badges, and that contributing to a site requires effort, how badges are designed will affect the incentives—therefore the participation and effort—elicited from strategic users on a site. We take a game-theoretic approach to badge design, analyzing the incentives created by widely used badge designs in a model in which winning a badge is valued, effort is costly, and potential contributors to the site endogenously decide whether or not to participate, and how much total effort to put into their contributions to the site. We analyze equilibrium existence, as well as equilibrium participation and effort, in an absolute standards mechanism Mα in which badges are awarded for meeting some absolute level of (observed) effort, and a relative standards mechanism Mρ corresponding to competitive standards, as in a top-ρ contributor badge. We find that equilibria always exist in both mechanisms, even when the value from winning a badge depends endogenously on the number of other winners. However, Mα has zero-participation equilibria for standards that are too high, whereas all equilibria in Mρ elicit nonzero participation for all possible ρ, provided that ρ is specified as a fixed number rather than as a fraction of actual contributors (note that the two are not equivalent in a setting with endogenous participation). Finally, we ask whether or not a site should explicitly announce the number of users winning a badge. The answer to this question is determined by the curvature of the value of winning the badge as a function of the number of other winners. In most online citizen science projects, a large proportion of participants contribute in small quantities. To investigate how low contributors differ from committed volunteers, we distributed a survey to members of the Old Weather project, followed by interviews with respondents selected according to a range of contribution levels. The studies reveal a complex relationship between motivations and contribution. Whilst high contributors were deeply engaged by social or competitive features, low contributors described a solitary experience of 'dabbling' in projects for short periods. Since the majority of participants exhibit this small-scale contribution pattern, there is great potential value in designing interfaces to tempt lone workers to complete 'just another page', or to lure early drop-outs back into participation. This includes breaking the work into components which can be tackled without a major commitment of time and effort, and providing feedback on the quality and value of these contributions. User participation emerged as a critical issue for collaborative and social recommender systems as well as for a range of other systems based on the power of user community. A range of mechanisms to encourage user participation in social systems has been proposed over the last few years; however, the impact of these mechanisms on users behavior in recommender systems has not been studied sufficiently. This paper investigates the impact of encouraging user participation in the context of CourseAgent, a community-based course recommender system. The recommendation power of CourseAgent is based on course ratings provided by a community of students. To increase the number of course ratings, CourseAgent applies an incentive mechanism which turns user feedback into a self-beneficial activity. In this paper, we describe the design and implementation of our course recommendation system and its incentive mechanism. We also report a dual impact of this mechanism on user behavior discovered in two user studies. The online encyclopedia Wikipedia is a highly successful “open content” project, written and maintained completely by volunteers. Little is known, however, about the motivation of these volunteers. Results from an online survey among 106 contributors to the German Wikipedia project are presented. Both motives derived from social sciences (perceived benefits, identification with Wikipedia, etc.) as well as perceived task characteristics (autonomy, skill variety, etc.) were assessed as potential predictors of contributors' satisfaction and self-reported engagement. Satisfaction ratings were particularly determined by perceived benefits, identification with the Wikipedia community, and task characteristics. Engagement was particularly determined by high tolerance for opportunity costs and by task characteristics, the latter effect being partially mediated by intrinsic motivation. Relevant task characteristics for contributors' engagement and satisfaction were perceived autonomy, task significance, skill vari...