Exploring the Relationship between Membership Turnover and Productivity in Online Communities

One of the more disruptive reforms associated with the modern Internet is the emergence of online communities working together on knowledge artefacts such as Wikipedia and OpenStreetMap. Recently it has become clear that these initiatives are vulnerable because of problems with membership turnover. This study presents a longitudinal analysis of 891 WikiProjects where we model the impact of member turnover and social capital losses on project productivity. By examining social capital losses we attempt to provide a more nuanced analysis of member turnover. In this context social capital is modelled from a social network perspective where the loss of more central members has more impact. We find that only a small proportion of WikiProjects are in a relatively healthy state with low levels of membership turnover and social capital losses. The results show that the relationship between social capital losses and project performance is U-shaped, and that member withdrawal has significant negative effect on project outcomes. The results also support the mediation of turnover rate and network density on the curvilinear relationship

Consequences of Content Diversity for Online Public Spaces for Local Communities

While there is significant potential for social technologies to strengthen local communities, creating viable online spaces for them remains difficult. Maintaining a reliable content stream is challenging for local communities with their bounded emphases and limited population of potential contributors. Some systems focus on specific information types (e.g. restaurant, events). Others allow many different information types. This paper reports our findings about the consequences of content diversity from a study of neighborhood-oriented Facebook groups. The findings raise questions about the viability of designs for local online communities that focus narrowly on single topics, goals, and audiences

NICE: Social translucence through UI intervention

ABSTRACT Social production systems such as Wikipedia rely on attracting and motivating volunteer contributions to be successful. One strong demotivating factor can be when an editor's work is discarded, or "reverted", by others. In this paper we demonstrate evidence of this effect and design a novel interface aimed at improving communication between the reverting and reverted editors. We deployed the interface in a controlled experiment on the live Wikipedia site, and report on changes in the behavior of 487 contributors who were reverted by editors using our interface. Our results suggest that simple interface modifications (such as informing Wikipedians that the editor they are reverting is a newcomer) can have substantial positive effects in protecting against contribution loss in newcomers and improving the quality of work done by more experienced contributors

Attention or Appreciation? The Impact of Feedback on Online Volunteering

We examine how different types of feedback influence online volunteer contributions in the context of online consultations for college entrance applications, which requires the volunteer counselor and the person receiving help (the counselee) to be online at the same time. We investigate the impact of two types of feedback on volunteers’ participation: 1) appreciation, as reflected in the number of positive ratings received by a counselor from counselees; and 2) attention, as reflected in the readership of a counselor’s profile page. We find that appreciation encourages the volunteer to engage in more helping behavior, likely because it can activate the volunteer’s altruistic motivation. In contrast, attention discourages volunteers to offer more help, possibly because they feel they have accomplished enough or because they feel passed over when they receive a lot of attention but few requests for consultations. The findings suggest that platform designers should encourage appreciation from those helped and provide more nuanced feedback about attention

An Automatic Group Formation Method to Foster Innovation in Collaborative Learning at Workplace

Despite group formation in learning environments is commonly and successfully approached, there is a gap in the research literature with respect to its application in corporative learning. Regarding that creativity is as an important factor to increase innovation in companies, in the present research, we propose a group formation method, considering preferred roles and functional diversity, aiming to improve creativity in collaborative learning at workplace. We employed Tabu Search algorithm to automatically form groups based on Nonaka\u27s knowledge creation theory and preferred roles from Belbin’s model. We performed a case study to compare the quality of socio-cognitive interactions duringcollaborative learning in groups formed by the proposed method and randomly formed groups. The results show that groups formed by preferred roles and functional diversity are more creative and present enhanced fluency and more elaborated products in comparison to randomly formed groups

Plataforma de I+D en sistemas de calificación y recomendación: arquitectura de referencia

En este trabajo se describe la arquitectura de una plataforma para la construcción de sistemas de calificación y recomendación, que será utilizada como vehículo para el desarrollo de proyectos de investigación y desarrollo en el tema. Esta arquitectura modela una familia de sistemas de recomendación basados en la calificación colaborativa de los recursos Web y en la información proporcionada por las redes sociales. Un sistema con estas características permite brindar al usuario recomendaciones adaptadas a su contexto. Se describirán los elementos principales que componen la arquitectura y los posibles mecanismos de interacción entre dichos elementos. Estos mecanismos permiten combinar diferentes fuentes de datos con el fin de poder brindar al usuario la posibilidad de calificar recursos Web, visualizar calificaciones sobre un recurso específico y obtener recomendaciones personalizadas. Se realizará el análisis de un modelo específico de calificación de recursos Web que involucra tres estrategias distintas de calificación, un conjunto de servicios necesarios para gestionar estas calificaciones y una interfaz como extensión del navegador web que permita la interacción entre los usuarios y los servicios de calificación y de recomendación. Además, se analizará la integración de las redes sociales con los servicios de calificación y recomendación planteados para ofrecer respuestas personalizadas

The Impact of Membership Overlap on the Survival of Online Communities

Online communities play an important role in society. In this paper, we study the effects of membership overlap on the survival of online communities. By analyzing the historical data of 5673 Wikia communities, we find that higher levels of membership overlap are positively associated with greater survival rate of online communities. Furthermore, we find that it is beneficial for new communities to have shared members who play a central role in other mature communities. These findings provide new insight into an important mechanism underlying successful online communities, contribute to theories of organization science, and provide several actionable steps for the hosts and creators of online communities

When Does Crowd Size Matter? The Influence of Diversity and Experience on the Effects of Crowd Size

One advantage of crowds over traditional teams is that crowds enable the assembling of a large number of individuals to address problems. The literature is unclear, however, about when crowd size leads to better outcomes. To better understand the effects of crowd size we conducted a study on the retention and performance of 4,317 articles in the WikiProject Film community. Results indicate that crowd composition, specifically diversity and experience, is vital to understanding when size leads to better retention and performance. Crowd size was positively related to retention and performance when crowds were high in diversity and experience. Retention was important to determining when crowd size led to better performance. Crowd size was positively related to performance when retention was low. Our results suggest that crowds benefit from their size when they are diverse, experienced, and have low retention rates.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113094/1/When Does Crowd Size Matters?.pdfDescription of When Does Crowd Size Matters?.pdf : Main articl

Participation of New Editors After Times of Shock on Wikipedia

User participation is vital to the success of collaborative crowdsourcing platforms such as Wikipedia. Previously user participation has been studied during “normal times”. However, less is known about participation following shocks that draw attention to an article. Such events can be recruiting opportunities due to increased attention; but can also pose a threat to the quality and control of the article and drive away newcomers. We study the collaborative dynamics of Wikipedia articles after times corresponding to shocks generated by drastic increases in attention as indicated by data from Google trends.We find that participation following such events is indeed different from participation during normal times–both newcomers and incumbents participate at higher rates during shocks. We also identify collaboration dynamics that mediate the effects of shocks on continued participation after the shock. The impact of shocks on participation is mediated by the amount of negative feedback given to newcomers in the form of reverted edits and the amount of coordination editors engage in through edits of the article’s talk page.National Science Foundation Grant No. IIS-1617820Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148429/1/Zhang et al. 2019.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148429/4/3253-Article Text-6302-1-10-20190531.pdfDescription of Zhang et al. 2019.pdf : Preprint versionDescription of 3253-Article Text-6302-1-10-20190531.pdf : Final Versio