Wikimedia Research/Showcase/Archive/2021/07

July 2021

Theme: Effects of campaigns to close content gaps

July 21, 2021 Video: YouTube

Content Growth and Attention Contagion in Information Networks. Addressing Information Poverty on Wikipedia

By Kai Zhu (McGill University, Canada)

Open collaboration platforms have fundamentally changed the way that knowledge is produced, disseminated, and consumed. In these systems, contributions arise organically with little to no central governance. Although such decentralization provides many benefits, a lack of broad oversight and coordination can leave questions of information poverty and skewness to the mercy of the system’s natural dynamics. Unfortunately, we still lack a basic understanding of the dynamics at play in these systems and specifically, how contribution and attention interact and propagate through information networks. We leverage a large-scale natural experiment to study how exogenous content contributions to Wikipedia articles affect the attention that they attract and how that attention spills over to other articles in the network. Results reveal that exogenously added content leads to significant, substantial, and long-term increases in both content consumption and subsequent contributions. Furthermore, we find significant attention spillover to downstream hyperlinked articles. Through both analytical estimation and empirically informed simulation, we evaluate policies to harness this attention contagion to address the problem of information poverty and skewness. We find that harnessing attention contagion can lead to as much as a twofold increase in the total attention flow to clusters of disadvantaged articles. Our findings have important policy implications for open collaboration platforms and information networks.

Related papers:

* Content Growth and Attention Contagion in Information Networks: Addressing Information Poverty on Wikipedia. Informations Systems Research (2020) (Link to pdf)

* Slides on figshare

Bridging Wikipedia’s Gender Gap. Quantifying and Assessing the Impact of Two Feminist Interventions

By Isabelle Langrock (University of Pennsylvania, USA)

Wikipedia has a well-known gender divide affecting its biographical content. This bias not only shapes social perceptions of knowledge, but it can also propagate beyond the platform as its contents are leveraged to correct misinformation, train machine-learning tools, and enhance search engine results. What happens when feminist movements intervene to try to close existing gaps? In this talk, we present a recent study of two popular feminist interventions designed to counteract digital knowledge inequality. Our findings show that the interventions are successful at adding content about women that would otherwise be missing, but they are less successful at addressing several structural biases that limit the visibility of women within Wikipedia. We argue for more granular and cumulative analysis of gender divides in collaborative environments and identify key areas of support that can further aid the feminist movements in closing Wikipedia’s gender gaps.