Do Experts or Crowd-Based Models Produce More Bias? Evidence from Encyclopedia Britannica and Wikipedia

Abstract

Organizations today can use both crowds and experts to produce knowledge. While prior work compares the accuracy of crowd-produced and expert-produced knowledge, we compare bias in these two models in the context of contested knowledge, which involves subjective, unverifiable, or controversial information. Using data from Encyclopaedia Britannica, authored by experts, and Wikipedia, an encyclopedia produced by an online community, we compare the slant and bias of pairs of articles on identical topics of US politics. Our slant measure is less (more) than zero when an article leans towards Democratic (Republican) viewpoints, while bias is the absolute value of the slant. We find that Wikipedia articles are more slanted towards Democratic views than are Britannica articles, as well as more biased. The difference in bias between a pair of articles decreases with more revisions. The bias on a per word basis hardly differs between the sources because Wikipedia articles tend to be longer than Britannica articles. These results highlight the pros and cons of each knowledge production model, help identify the scope of the empirical generalization of prior studies comparing the information quality of the two production models, and offer implications for organizations managing crowd-based knowledge production.

What Is Different About Digital Strategy? From Quantitative to Qualitative Change

“…In these communities, remotely located individuals are able to collaborate using digital technology that enables coordination through global visibility of coding work in progress as well as tools for managing dependencies and communication among contributors. Scholars have shown that in certain domains of the software industry, this form of organizing-an unambiguous offspring of the connectivity enabled by digitizationenables the aggregation of efforts from numerous contributors and provides credible alternatives to what for-profit firms do (e.g., Greenstein andZhu 2018, Klapper andReitzig 2018). The possibility of purely algorithmic solutions to the universal problems of organizing-for example, division of labor and integration of effort-appears to be at the verge of realization in these systems (Puranam et al 2014).…”

Does Copyright Affect Reuse? Evidence from Google Books and Wikipedia

“…Third, Baseball Digest frequently runs profiles of baseball players and teams, including detailed articles, interviews, and player images. Such biographical information forms the foundation of any encyclopedia (Greenstein and Zhu 2017) and is, therefore, particularly likely to be reused on Wikipedia. Finally, each revision of a Wikipedia page is archived and publicly accessible.…”

Storm Crowds: Evidence from Zooniverse on Crowd Contribution Design

“…Indeed, the term 'wiki' refers precisely to this feature of the site. By contrast, entries to Encyclopedia Britannica were typically sourced with little to no monetary reward from experts but those experts were required to provide a complete article (Greenstein and Zhu 2017). This has motivated our study into whether this design component -notably, the divisibility of contributions (i.e., whether contributing tasks are bundled together or can be carried out selectively) -is a factor in the level and quality of contributions in crowdsourcing.…”