Product diffusion through on-demand information-seeking behaviour. Issue 139 (28th February 2018)

• Record Type: Journal Article
• Authors: Riedl, Christoph; Bjelland, Johannes; Canright, Geoffrey; Iqbal, Asif; Engø-Monsen, Kenth; Qureshi, Taimur; Sundsøy, Pål Roe; Lazer, David
• Is Part Of: Journal of the Royal Society interface. Volume 15:Issue 139(2018)
• Publication Date: 2018-02-28
• Subjects: diffusion -- computational social science -- social networks -- complex systems; Physical sciences -- Research -- Periodicals; Life sciences -- Research -- Periodicals; Interdisciplinary research -- Periodicals; 570.5
• DOI: 10.1098/rsif.2017.0751
• Languages: English
• ISSNs: 1742-5689

Abstract

Abstract : Most models of product adoption predict S-shaped adoption curves. Here we report results from two country-scale experiments in which we find linear adoption curves. We show evidence that the observed linear pattern is the result of active information-seeking behaviour: individuals actively pulling information from several central sources facilitated by modern Internet searches. Thus, a constant baseline rate of interest sustains product diffusion, resulting in a linear diffusion process instead of the S-shaped curve of adoption predicted by many diffusion models. The main experiment seeded 70 000 (48 000 in Experiment 2) unique voucher codes for the same product with randomly sampled nodes in a social network of approximately 43 million individuals with about 567 million ties. We find that the experiment reached over 800 000 individuals with 80% of adopters adopting the same product—a winner-take-all dynamic consistent with search engine driven rankings that would not have emerged had the products spread only through a network of social contacts. We provide evidence for (and characterization of) this diffusion process driven by active information-seeking behaviour through analyses investigating (a) patterns of geographical spreading; (b) the branching process; and (c) diffusion heterogeneity. Using data on adopters' geolocation we show that social spreading is highly localized, while on-demand diffusion is geographically independent. We also show that cascades started by individuals who actively pull information from central sources are more effective at spreading the product among their peers.