Gender differences within the German-language Wikipedia

The Wikipedia project constitutes the currently most-used and most comprehensive online encyclopedia in the world (Schneider, 2008, p. 35) and is advertising itself as free and open for everyone, and in terms of an encyclopedia as diverse and balanced at all levels. But from a gender perspective there is a huge discrepancy in sex ratio within Wikipedia’s community. In 2005, researchers at University of Würzburg found that women constitute only 10 % of German-language Wikipedia authors (Schroer&Hertel, 2009, p. 104). This fact leads to the presumption, that Wikipedia’s reflection of the world mediates and interprets a mainly male conception of the world and thus displays an inequality with reference to modern society. Proceeding from the assumption that women and men have different communication behaviours as well as different perceptions and interpretations of communication in almost all aspects of social interaction including e.g. conversational strategies, conflict management and negotiation skills, we hypothesize that these different ways of communication significantly affect the motivation of female Wikipedia contributors

Wikis supporting PLM and Technical Documentation

Over the last years, Wikis have arisen as powerful tools for collaborative documentation on the Internet. The Encyclopaedia Wikipedia has become a reference, and the power of community editing in a Wiki allows for capture of knowledge from contributors all over the world. Use of a Wiki for Technical Documentation, along with hyper-links to other data sources such as a Product Lifecycle Management (PLM) system, provides a very effective collaboration tool as information can be easily feed into the system throughout the project life-cycle. In particular for software- and hardware projects with rapidly evolving documentation, the Wiki approach has proved to be successful. Certain Wiki implementations, such as TWiki, are project-oriented and include functionality such as automatic page revisioning. This paper addresses the use of TWiki to document hardware and software projects at CERN, from the requirements and brain-storming phase to end-product documentation. 2 examples are covered: large scale engineering for the ATLAS Experiment, and a network management software project

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

Social Interactions vs Revisions, What is important for Promotion in Wikipedia?

In epistemic community, people are said to be selected on their knowledge contribution to the project (articles, codes, etc.) However, the socialization process is an important factor for inclusion, sustainability as a contributor, and promotion. Finally, what does matter to be promoted? being a good contributor? being a good animator? knowing the boss? We explore this question looking at the process of election for administrator in the English Wikipedia community. We modeled the candidates according to their revisions and/or social attributes. These attributes are used to construct a predictive model of promotion success, based on the candidates's past behavior, computed thanks to a random forest algorithm. Our model combining knowledge contribution variables and social networking variables successfully explain 78% of the results which is better than the former models. It also helps to refine the criterion for election. If the number of knowledge contributions is the most important element, social interactions come close second to explain the election. But being connected with the future peers (the admins) can make the difference between success and failure, making this epistemic community a very social community too

Fostering Public Good Contributions with Symbolic Awards: A Large-Scale Natural Field Experiment at Wikipedia

This natural field experiment tests the effects of purely symbolic awards on volunteer retention in a public goods context. The experiment is conducted at Wikipedia, which faces declining editor retention rates, particularly among newcomers. Randomization assures that award receipt is orthogonal to previous performance. The analysis reveals that awards have a sizeable effect on newcomer retention, which persists over the four quarters following the initial intervention. This is noteworthy for indicating that awards for volunteers can be effective even if they have no impact on the volunteers’ future career opportunities. The awards are purely symbolic, and the status increment they produce is limited to the recipients’ pseudonymous online identities in a community they have just recently joined. The results can be explained by enhanced self-identification with the community, but they are also in line with recent findings on the role of status and reputation, recognition, and evaluation potential in online communities. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2016.2540 . This paper was accepted by John List, behavioral economics

Beyond opening up the black box: Investigating the role of algorithmic systems in Wikipedian organizational culture

Scholars and practitioners across domains are increasingly concerned with algorithmic transparency and opacity, interrogating the values and assumptions embedded in automated, black-boxed systems, particularly in user-generated content platforms. I report from an ethnography of infrastructure in Wikipedia to discuss an often understudied aspect of this topic: the local, contextual, learned expertise involved in participating in a highly automated social-technical environment. Today, the organizational culture of Wikipedia is deeply intertwined with various data-driven algorithmic systems, which Wikipedians rely on to help manage and govern the "anyone can edit" encyclopedia at a massive scale. These bots, scripts, tools, plugins, and dashboards make Wikipedia more efficient for those who know how to work with them, but like all organizational culture, newcomers must learn them if they want to fully participate. I illustrate how cultural and organizational expertise is enacted around algorithmic agents by discussing two autoethnographic vignettes, which relate my personal experience as a veteran in Wikipedia. I present thick descriptions of how governance and gatekeeping practices are articulated through and in alignment with these automated infrastructures. Over the past 15 years, Wikipedian veterans and administrators have made specific decisions to support administrative and editorial workflows with automation in particular ways and not others. I use these cases of Wikipedia's bot-supported bureaucracy to discuss several issues in the fields of critical algorithms studies, critical data studies, and fairness, accountability, and transparency in machine learning -- most principally arguing that scholarship and practice must go beyond trying to "open up the black box" of such systems and also examine sociocultural processes like newcomer socialization.Comment: 14 pages, typo fixed in v

Building Collaborative Capacities in Learners: The M/cyclopedia Project Revisited

In this paper we trace the evolution of a project using a wiki-based learning environment in a tertiary education setting. The project has the pedagogical goal of building learners’ capacities to work effectively in the networked, collaborative, creative environments of the knowledge economy. The paper explores the four key characteristics of a ‘produsage’ environment and identifies four strategic capacities that need to be developed in learners to be effective ‘produsers’ (user-producers). A case study is presented of our experiences with the subject New Media Technologies, run at Queensland University of Technology, Brisbane, Australia. This progress report updates our observations made at the 2005 WikiSym conference

SUPER: Towards the Use of Social Sensors for Security Assessments and Proactive Management of Emergencies

Social media statistics during recent disasters (e.g. the 20 million tweets relating to 'Sandy' storm and the sharing of related photos in Instagram at a rate of 10/sec) suggest that the understanding and management of real-world events by civil protection and law enforcement agencies could benefit from the effective blending of social media information into their resilience processes. In this paper, we argue that despite the widespread use of social media in various domains (e.g. marketing/branding/finance), there is still no easy, standardized and effective way to leverage different social media streams -- also referred to as social sensors -- in security/emergency management applications. We also describe the EU FP7 project SUPER (Social sensors for secUrity assessments and Proactive EmeRgencies management), started in 2014, which aims to tackle this technology gap