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      The role of geography in the complex diffusion of innovations

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          Abstract

          The urban–rural divide is increasing in modern societies calling for geographical extensions of social influence modelling. Improved understanding of innovation diffusion across locations and through social connections can provide us with new insights into the spread of information, technological progress and economic development. In this work, we analyze the spatial adoption dynamics of iWiW, an Online Social Network (OSN) in Hungary and uncover empirical features about the spatial adoption in social networks. During its entire life cycle from 2002 to 2012, iWiW reached up to 300 million friendship ties of 3 million users. We find that the number of adopters as a function of town population follows a scaling law that reveals a strongly concentrated early adoption in large towns and a less concentrated late adoption. We also discover a strengthening distance decay of spread over the life-cycle indicating high fraction of distant diffusion in early stages but the dominance of local diffusion in late stages. The spreading process is modelled within the Bass diffusion framework that enables us to compare the differential equation version with an agent-based version of the model run on the empirical network. Although both model versions can capture the macro trend of adoption, they have limited capacity to describe the observed trends of urban scaling and distance decay. We find, however that incorporating adoption thresholds, defined by the fraction of social connections that adopt a technology before the individual adopts, improves the network model fit to the urban scaling of early adopters. Controlling for the threshold distribution enables us to eliminate the bias induced by local network structure on predicting local adoption peaks. Finally, we show that geographical features such as distance from the innovation origin and town size influence prediction of adoption peak at local scales in all model specifications.

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          Most cited references 35

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              A New Product Growth for Model Consumer Durables

               Frank M. Bass (1969)
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                Author and article information

                Contributors
                lengyel.balazs@krtk.mta.hu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                15 September 2020
                15 September 2020
                2020
                : 10
                Affiliations
                [1 ]GRID grid.116068.8, ISNI 0000 0001 2341 2786, Department of Civil and Environmental Engineering, , Massachusetts Institute of Technology, ; Cambridge, MA 02139 USA
                [2 ]GRID grid.445629.8, ISNI 0000 0001 2287 361X, International Business School Budapest, ; Budapest, 1037 Hungary
                [3 ]GRID grid.424949.6, ISNI 0000 0001 1704 1923, Agglomeration and Social Networks Lendület Research Group, Centre for Economic- and Regional Studies, , Institute of Economics, ; Budapest, 1097 Hungary
                [4 ]GRID grid.17127.32, ISNI 0000 0000 9234 5858, Institute of Advanced Studies, , Corvinus University of Budapest, ; Budapest, 1093 Hungary
                [5 ]GRID grid.8391.3, ISNI 0000 0004 1936 8024, Computer Science Department, , University of Exeter, ; Exeter, EX4 4QF UK
                [6 ]GRID grid.83440.3b, ISNI 0000000121901201, The Bartlett Centre for Advanced Spatial Analysis, , University College London, ; London, WC1E 6BT UK
                [7 ]GRID grid.5146.6, ISNI 0000 0001 2149 6445, Department of Network and Data Science, , Central European University, ; Budapest, 1051 Hungary
                [8 ]GRID grid.47840.3f, ISNI 0000 0001 2181 7878, Department of City and Regional Planning, , University of California at Berkeley, ; Berkeley, CA 94720 USA
                [9 ]GRID grid.184769.5, ISNI 0000 0001 2231 4551, Energy Analysis and Environmental Impacts Division, , Lawrence Berkeley National Laboratory, ; Berkeley, Ca 94720 USA
                Article
                72137
                10.1038/s41598-020-72137-w
                7492253
                db0e91ac-0833-430f-93d1-ab5f3f41c404
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: Rosztoczy Foundation
                Funded by: Eötvös Fellowship of the Hungarian State
                Funded by: National Research, Development and Innovation Office
                Award ID: KH130502
                Award Recipient :
                Funded by: Newton International Fellowship
                Award ID: NF17050
                Award Recipient :
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                © The Author(s) 2020

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                socioeconomic scenarios, environmental social sciences

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