File:Wikimedia Research Showcase - October 2016.webm

Wikimedia Research Showcase - October 19, 2016; mw:Wikimedia_Research/Showcase#October_2016:

• Human centered design for using and editing structured data in Wikipedia infoboxes By User:Charlie_Kritschmar_(WMDE) UX Intern, Wikimedia Deutschland
  • Wikidata is a Wikimedia project which stores structured data to be used by other Wikimedia projects like Wikipedia. Currently, integrating its data in Wikipedia is difficult for users, since there’s no predefined way to do so and requires some technical knowledge. To tackle these issues, human-centered design methods were applied to find needs from which solutions were generated and evaluated with the help of the community. The concept may serve as a basis which may be implemented into various Wiki projects in the future to make editing Wikidata from within another Wikimedia project more user-friendly and improve the project’s acceptance in the community.

• Emergent Work in Wikipedia By Ofer Arazy (University of Haifa)
  • Online production communities present an exciting opportunity for investigating novel organizational forms. Extant theoretical accounts of knowledge co-production point to organizational policies, norms, and communication as key mechanisms enabling the coordination of work. Yet, in practice participants in initiatives such as Wikipedia are often occasional contributors who are unaware of community policies and do not communicate with other members. How then is work coordinated and how does the organization maintain stability in the face of dynamics in individuals’ task enactment? In this study we develop a conceptualization of emergent roles - the prototypical activity patterns that organically emerge from individuals’ spontaneous actions – and investigate the temporal dynamics of emergent role behaviors. Conducing a multi-level large-scale empirical study stretching over a decade, we tracked co-production of a thousand Wikipedia articles, logging two hundred thousand distinct participants and seven hundred thousand co-production activities. Using a combination of manual tagging and machine learning, we annotated each activity type, and then clustered participants’ activity profiles to arrive at seven prototypical emergent roles. Our analysis shows that participants’ behavior is turbulent, with substantial flow in and out of co-production work and across roles. Our findings at the organizational level, however, show that work is organized around a highly stable set of emergent roles, despite the absence of traditional stabilizing mechanisms such as pre-defined work procedures or role expectations. We conceptualize this dualism in emergent work as “Turbulent Stability”. Further analyses suggest that co-production is artifact-centric, where contributors mutually adjust according to the artifact’s changing needs. Our study advances the theoretical understandings of self-organizing knowledge co-production and particularly the nature of emergent roles.