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

Evolution of Privacy Loss in Wikipedia

The cumulative effect of collective online participation has an important and adverse impact on individual privacy. As an online system evolves over time, new digital traces of individual behavior may uncover previously hidden statistical links between an individual's past actions and her private traits. To quantify this effect, we analyze the evolution of individual privacy loss by studying the edit history of Wikipedia over 13 years, including more than 117,523 different users performing 188,805,088 edits. We trace each Wikipedia's contributor using apparently harmless features, such as the number of edits performed on predefined broad categories in a given time period (e.g. Mathematics, Culture or Nature). We show that even at this unspecific level of behavior description, it is possible to use off-the-shelf machine learning algorithms to uncover usually undisclosed personal traits, such as gender, religion or education. We provide empirical evidence that the prediction accuracy for almost all private traits consistently improves over time. Surprisingly, the prediction performance for users who stopped editing after a given time still improves. The activities performed by new users seem to have contributed more to this effect than additional activities from existing (but still active) users. Insights from this work should help users, system designers, and policy makers understand and make long-term design choices in online content creation systems

Jointly they edit: examining the impact of community identification on political interaction in Wikipedia

In their 2005 study, Adamic and Glance coined the memorable phrase "divided they blog", referring to a trend of cyberbalkanization in the political blogosphere, with liberal and conservative blogs tending to link to other blogs with a similar political slant, and not to one another. As political discussion and activity increasingly moves online, the power of framing political discourses is shifting from mass media to social media. Continued examination of political interactions online is critical, and we extend this line of research by examining the activities of political users within the Wikipedia community. First, we examined how users in Wikipedia choose to display (or not to display) their political affiliation. Next, we more closely examined the patterns of cross-party interaction and community participation among those users proclaiming a political affiliation. In contrast to previous analyses of other social media, we did not find strong trends indicating a preference to interact with members of the same political party within the Wikipedia community. Our results indicate that users who proclaim their political affiliation within the community tend to proclaim their identity as a "Wikipedian" even more loudly. It seems that the shared identity of "being Wikipedian" may be strong enough to triumph over other potentially divisive facets of personal identity, such as political affiliation.Comment: 33 pages, 5 figure

Wikipedia Conflict Representation in Articles of War: A critical discourse analysis of current, on-going, socio-political Wikipedia articles about war

With the help of a discourse-historical approach, a textual corpus composed of the talk pages of three controversial, socio-political Wikipedia articles about ongoing wars was analyzed in order to shed light on the way in which conflict is represented through the editing and discussion process. Additionally, a rational discourse was employed in order to unravel communication distortions within the editing process in an attempt to improve communication and consensus-seeking. Finally, semi-structured interviews of participating contributors within studied articles were used in order to better understand Wikipedian experience in a controversial collaboration scenario. Results unveiled a set of discursive practices in which Wikipedians participate, as well as the creation of a Wikipedian argumentation topoi framework useful for further Wikipedia-specific discourse analysis involving the content change-retain negotiation process

Topics of Bioengineering in Wikipedia

The present report aims to give a snapshot of how topics from the field of bioengineering (bioinformatics, bioprocess systems, biomedical engineering, biotechnology, etc.) are currently covered in the free electronic encyclopedia Wikipedia. It also offers insights and information about what Wikipedia is, how it functions, how and when to cite Wikipedian articles, if necessary. Several external wikis, devoted to topics of bioengineering, are also listed and reviewed

Making sense of the German Wikipedia community

This article presents the findings from a qualitative study of the German Wikipedia community, focusing on how people engaged with Wikipedia make sense of norms, collaborative practices and means of regulation within the community. The study highlights the strong focus on the quality of the end-product (the encyclopedia) in the German community, stressing that article quality is seen as more important than the wiki-process as such. As the community has grown, an increasing number of rules and mechanisms have been deployed to resolve various issues and conflicts, however the interviewees do not perceive Wikipedia as being bureaucratic, but rather describe it as a “rule-governed anarchy”. The findings suggest that people contribute for a variety of reasons, yet point to reactions from and interactions with fellow Wikipedians as one of the strongest motivational drivers for participation

The role of cognitive conflict in open-content collaboration

IS research on participant’s motivation1 in Knowledge Management System have paid relatively limited attention to the effect of diversifying the technological artifacts while they focused more on identifying the generic motivational factors that apply across the varying contexts. However, the manifest success of disruptive collaboration system outside of the corporate boundaries such as Wikipedia calls for our extended attention to the motivational factors that may not be emergent without the provision of context and artifacts that challenge the assumptions made by KMS within the organizational setting. Through the online survey of 100 Wikipedians, this study evaluates the effect of one novel construct (i.e., socio-cognitive conflict) proposed by Cress and Kimmerle (2008) as an example of such emergent motivation made explicit by maneuvering specific design of collaboration system which otherwise would remain immaterial. In parallel, the analysis also explores the generic motivational constructs the effects of which have been extensively studied within organizational contexts but not sufficiently examined outside of such boundaries