Arguments about deletion

Schneider, Jodi; Samp, Krystian; Passant, Alexandre; Decker, Stefan

doi:10.1145/2441776.2441897

Cited by 27 publications

(9 citation statements)

References 24 publications

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“…Updating our understanding of open source projects as a social computing phenomena is critical not only for its own sake, but because previous studies of open source projects are sometimes operationalized in literature as a conceptual anchor that informs work in other collaborative settings [e.g., 17,32,37,40,51] or serves as a site of study to inform concepts that are not unique to open source [e.g., 30,31,63,66]. Those studies do not advance our understanding of open source projects specifically, but they build their conceptual cases using a potentially outdated understanding of "how open source works".…”

Section: Prior Work On Open Sourcementioning

confidence: 99%

Eight Observations and 24 Research Questions About Open Source Projects

Link

Lumbard

Goggins

2018

Proc. ACM Hum.-Comput. Interact.

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The rapid acceleration of corporate engagement with open source projects is drawing out new ways for CSCW researchers to consider the dynamics of these projects. Research must now consider the complex ecosystems within which open source projects are situated, including issues of for-profit motivations, brokering foundations, and corporate collaboration. Localized project considerations cannot reveal broader workings of an open source ecosystem, yet much empirical work is constrained to a local context. In response, we present eight observations from our eight-year engaged field study about the changing nature of open source projects. We ground these observations through 24 research questions that serve as primers to spark research ideas in this new reality of open source projects. This paper contributes to CSCW in social and crowd computing by delivering a rich and fresh look at corporately-engaged open source projects with a call for renewed focus and research into newly emergent areas of interest. CCS Concepts: • General and reference → Surveys and overviews; • Information systems → Open source software; • Human-centered computing → Field studies; Open source software; Computer supported cooperative work; • Software and its engineering → Open source model; • Social and professional topics → Socio-technical systems;

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Section: Prior Work On Open Sourcementioning

confidence: 99%

Eight Observations and 24 Research Questions About Open Source Projects

Link

Lumbard

Goggins

2018

Proc. ACM Hum.-Comput. Interact.

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“…Some have argued, for example, that task interdependence and geographical distribution in some cases increase conflict in free and open-source software development teams. Schneider et al (Schneider et al 2013) found that arguing with Wikipedia collaborators on the basis of "personal preference and inappropriate analogy to other cases," rather than adhering to community norms and conventions, can be seen by others in the community as problematic, and, thus, fuel conflicts. In addition, disagreements among leaders (e.g.…”

Section: Understanding and Addressing Online Conflictmentioning

confidence: 99%

Managing Conflict in Online Debate Communities: Foregrounding Moderators' Beliefs and Values on Kialo

Beck¹,

Neupane²,

Carroll³

2018

Preprint

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Kialo is a novel peer production system focused on pro/con debate construction. Teams of moderators vet and accept claims submitted by writers. Moderators also edit and refactor debates as they grow. Thus, moderators play a critical role in cultivating and maintaining debates. Conflict between moderators is typical. It is a feature of argumentation and debate. However, not all conflict is productive. Conflict between moderators can undermine collaboration (by distracting from the task of managing debates) and drive attrition (by discouraging participation on the site altogether). Based on a ten-month participant observation on Kialo, we identify a common source of conflict between moderators: adversarial beliefs and values. Moderators are not neutral participants on Kialo. They take positions on debate topics. We suggest foregrounding these positions, which are potential sources of conflict, through interface design as a scalable solution to conflict management.

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“…In [25] the authors conclude that collectives in Wikipedia follow their self-imposed rules regarding well defined and formalized processes, such as featured articles. Schneider et al [26,27,28,29] discussed multiple different aspects and the importance of consensus finding on Wikipedia and the Social Semantic Web, by analyzing the history of articles in said systems, further strengthening the need for tools and analyses to be able to better understand and support digital collaborative endeavors.…”

Section: Collaborative Authoring Systemsmentioning

confidence: 99%

How to apply Markov chains for modeling sequential edit patterns in collaborative ontology-engineering projects

Walk

Singer

Strohmaier

et al. 2015

International Journal of Human-Computer Studies

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With the growing popularity of large-scale collaborative ontologyengineering projects, such as the creation of the 11 th revision of the International Classification of Diseases, we need new methods and insights to help project-and community-managers to cope with the constantly growing complexity of such projects. In this paper, we present a novel application of Markov chains to model sequential usage patterns that can be found in the change-logs of collaborative ontology-engineering projects. We provide a detailed presentation of the analysis process, describing all the required steps that are necessary to apply and determine the best fitting Markov chain model. Amongst others, the model and results allow us to identify structural properties and regularities as well as predict future actions based on usage sequences. We are specifically interested in determining the appropriate Markov chain orders which postulate on how many previous actions future ones depend on. To demonstrate the practical usefulness of the extracted Markov chains we conduct sequential pattern analyses on a large-scale collaborative ontology-engineering dataset, the International Classification of Diseases in its 11 th revision. To further expand on the usefulness of the presented analysis, we show that the collected sequential patterns provide potentially actionable information for user-interface designers, ontology-engineering tool developers and project-managers to monitor, coordinate and dynamically adapt to the natural development processes that occur when collaboratively engineering an ontology. We hope that presented work will spur a new line of ontology-development tools, evaluation-techniques and new insights, further taking the interactive nature of the collaborative ontology-engineering process into consideration.

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Arguments about deletion

Cited by 27 publications

References 24 publications

Eight Observations and 24 Research Questions About Open Source Projects

Eight Observations and 24 Research Questions About Open Source Projects

Managing Conflict in Online Debate Communities: Foregrounding Moderators' Beliefs and Values on Kialo

How to apply Markov chains for modeling sequential edit patterns in collaborative ontology-engineering projects

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