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.
Besides individual incentives, previous studies also stressed the importance of the initial period of socialization in online groups. A successful early socialization experience is associated with, and sometimes even predicts, increased engagement in mailing lists @cite_4 , newsgroups @cite_13 , social networks @cite_23 , and Wikipedia @cite_27 @cite_2 , to cite a few. However, the causal structure between socialization, motivation, and participation is still not entirely clear. Strong motivational factors, perhaps in conjunction with individual-level skills @cite_0 , may be the cause for both a successful early socialization stage and a later long-term participation. To further establish a causal connection, controlled and field experiments on groups of limited size have been performed, with encouraging results: sharing in a digital information good is increased by social incentives @cite_21 , personal messages improve the retention of newcomers to Wikipedia who had their edits rejected @cite_3 , and top contributors in a Q &A community contributed more on the long term if they had received a personalized socialization experience @cite_11 .
@cite_4 @cite_21 @cite_3 @cite_0 @cite_27 @cite_23 @cite_2 @cite_13 @cite_11
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Online communities in the form of message boards, listservs, and newsgroups continue to represent a considerable amount of the social activity on the Internet. Every year thousands of groups ourish while others decline into relative obscurity; likewise, millions of members join a new community every year, some of whom will come to manage or moderate the conversation while others simply sit by the sidelines and observe. These processes of group formation, growth, and dissolution are central in social science, and in an online venue they have ramifications for the design and development of community software In this paper we explore a large corpus of thriving online communities. These groups vary widely in size, moderation and privacy, and cover an equally diverse set of subject matter. We present a broad range of descriptive statistics of these groups. Using metadata from groups, members, and individual messages, we identify users who post and are replied-to frequently by multiple group members; we classify these high-engagement users based on the longevity of their engagements. We show that users who will go on to become long-lived, highly-engaged users experience significantly better treatment than other users from the moment they join the group, well before there is an opportunity for them to develop a long-standing relationship with members of the group We present a simple model explaining long-term heavy engagement as a combination of user-dependent and group-dependent factors. Using this model as an analytical tool, we show that properties of the user alone are sufficient to explain 95 of all memberships, but introducing a small amount of per-group information dramatically improves our ability to model users belonging to multiple groups. The goal of this research is to understand how generalized exchange systems emerge when information, as the object of exchange, produces a collective good. When individuals contribute information for a collective benefit, it can create a group-generalized exchange system that involves a social dilemma. I argue that two properties of information, replication and high jointness of supply, are crucial for understanding the nature of the social dilemma in these exchange systems. Combined with low-cost contributions, these special features of information can allow social psychological selective incentives to significantly encourage cooperation. Experiments were conducted to examine the independent effects of two social psychological selective incentives (social approval and observational cooperation) on sharing behavior in a generalized information exchange system. The results indicate that observing high levels of cooperative behavior is beneficial in the short run, but ultimately it only leads to moderately higher levels of cooperation than when individuals cannot observe cooperative behavior. On the other hand, when individuals receive either high or low levels of social approval, it has a very positive, significant impact on cooperative behavior. This research has implications for real-world generalized information exchange systems such as those found on the Internet. In addition, the theory and results in this study can also be extended to public goods that share the features of low-costs contributions, replication, and high jointness of supply. Unlike traditional firms, open collaborative systems rely on volunteers to operate, and many communities struggle to maintain enough contributors to ensure the quality and quantity of content. However, Wikipedia has historically faced the exact opposite problem: too much participation, particularly from users who, knowingly or not, do not share the same norms as veteran Wikipedians. During its period of exponential growth, the Wikipedian community developed specialized socio-technical defense mechanisms to protect itself from the negatives of massive participation: spam, vandalism, falsehoods, and other damage. Yet recently, Wikipedia has faced a number of high-profile issues with recruiting and retaining new contributors. In this paper, we first illustrate and describe the various defense mechanisms at work in Wikipedia, which we hypothesize are inhibiting newcomer retention. Next, we present results from an experiment aimed at increasing both the quantity and quality of editors by altering various elements of these defense mechanisms, specifically pre-scripted warnings and notifications that are sent to new editors upon reverting or rejecting contributions. Using logistic regressions to model new user activity, we show which tactics work best for different populations of users based on their motivations when joining Wikipedia. In particular, we found that personalized messages in which Wikipedians identified themselves in active voice and took direct responsibility for rejecting an editor’s contributions were much more successful across a variety of outcome metrics than the current messages, which typically use an institutional and passive voice. Publisher Summary This chapter focuses on individual differences in human–computer interaction. Differences among users have not been a major concern of commercial computer interface designers. Even behavioral scientists usually select narrowly defined user samples to minimize experimental error when comparing the mean performance of different systems. Those behavioral studies that have analyzed differences among users often have produced descriptive results rather than prescriptions for interface design. In the future, interface designers should focus a great deal of attention on the differences among potential users for three reasons. First, individual differences usually play a major role in determining whether humans can use a computer to perform a job effectively. Second, personnel selection testing, the standard solution to problems of job-related individual differences, cannot be applied to many settings where humans interact with computers. The third reason for designers to be concerned with individual differences is that the technology has reached the point where it is possible to accommodate more user differences. 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 member's 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. Social networking sites (SNS) are only as good as the content their users share. Therefore, designers of SNS seek to improve the overall user experience by encouraging members to contribute more content. However, user motivations for contribution in SNS are not well understood. This is particularly true for newcomers, who may not recognize the value of contribution. Using server log data from approximately 140,000 newcomers in Facebook, we predict long-term sharing based on the experiences the newcomers have in their first two weeks. We test four mechanisms: social learning, singling out, feedback, and distribution. In particular, we find support for social learning: newcomers who see their friends contributing go on to share more content themselves. For newcomers who are initially inclined to contribute, receiving feedback and having a wide audience are also predictors of increased sharing. On the other hand, singling out appears to affect only those newcomers who are not initially inclined to share. The paper concludes with design implications for motivating newcomer sharing in online communities. 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. Although many off-line organizations give their employees training, mentorship, a cohort and other socialization experiences that improve their retention and productivity, online production communities rarely do this. This paper describes the planning, execution and evaluation of a socialization regime for an online technical support community. In a two-phase project, we first automatically identified from participants' early behavior, those with high potential to become core members. We then designed, delivered and experimentally evaluated socialization experiences intended to build commitment and competence among these potential core members. We were able to identify potential core members with high accuracy from only two weeks of behavior. A year later, those classified as potential core members participated in the community ten times more actively than those not identified. In an evaluation experiment, some potential core members were randomly assigned to receive socialization experiences, while others were not. A year later, those who had participated in the socialization regime contributed more answers in the community compared to those in the control condition. The socialization experiences, however, undercut their sense of connection to the community and the quality of their contributions. We discuss what was effective and what could be improved in designing socialization experiences for online groups.