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

Kai Zhu (), Dylan Walker () and Lev Muchnik ()
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Kai Zhu: Desautels Faculty of Management, McGill University, Montreal, Quebec H3A 1G5, Canada;
Dylan Walker: Questrom School of Business, Boston University, Boston, Massachusetts 02215;
Lev Muchnik: Jerusalem School of Business Administration, The Hebrew University of Jerusalem, 91905 Jerusalem, Israel

Information Systems Research, 2020, vol. 31, issue 2, 491-509

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.

Keywords: user-generated content; open collaboration platform; information consumption; attention contagion; spillover effect (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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