Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 491-509 |
| Number of pages | 19 |
| Journal | Information Systems Research |
| Volume | 31 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2020 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 1 No Poverty
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Attention contagion
- Information consumption
- Open collaboration platform
- Spillover effect
- User-generated content
All Science Journal Classification (ASJC) codes
- Management Information Systems
- Information Systems
- Computer Networks and Communications
- Information Systems and Management
- Library and Information Sciences
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