Accelerating dynamics of collective attention - PMC
Skip to main content
Official websites use .gov
.gov website belongs to an official<br>government organization in the United States.
Secure .gov websites use HTTPS
A lock (
Lock
Locked padlock icon
) or https:// means you've safely<br>connected to the .gov website. Share sensitive<br>information only on official, secure websites.
Search PMC Full-Text Archive
Search in PMC
Journal List
User Guide
PERMALINK
Copy
As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with,<br>the contents by NLM or the National Institutes of Health.
Learn more:<br>PMC Disclaimer
PMC Copyright Notice
Nat Commun<br>. 2019 Apr 15;10:1759. doi: 10.1038/s41467-019-09311-w
Accelerating dynamics of collective attention
Philipp Lorenz-Spreen<br>Philipp Lorenz-Spreen
1Institute of Theoretical Physics, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin, Germany
2Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
Find articles by Philipp Lorenz-Spreen
1,2, Bjarke Mørch Mønsted<br>Bjarke Mørch Mønsted
3Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, 2800 Kgs., Lyngby, Denmark
Find articles by Bjarke Mørch Mønsted
3, Philipp Hövel<br>Philipp Hövel
1Institute of Theoretical Physics, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin, Germany
4School of Mathematical Sciences, University College Cork, Western Road, Cork, T12 XF62 Ireland
Find articles by Philipp Hövel
1,4,✉,#, Sune Lehmann<br>Sune Lehmann
3Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, 2800 Kgs., Lyngby, Denmark
5Center for Social Data Science, University of Copenhagen, Øster Farimagsgade 5, 1353 Copenhagen K., Denmark
Find articles by Sune Lehmann
3,5,✉,#
Author information
Article notes
Copyright and License information
1Institute of Theoretical Physics, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin, Germany
2Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
3Department of Applied Mathematics and Computer Science, Technical University of Denmark, Richard Petersens Plads, 2800 Kgs., Lyngby, Denmark
4School of Mathematical Sciences, University College Cork, Western Road, Cork, T12 XF62 Ireland
5Center for Social Data Science, University of Copenhagen, Øster Farimagsgade 5, 1353 Copenhagen K., Denmark
✉Corresponding author.
#Contributed equally.
Received 2018 Oct 2; Accepted 2019 Mar 5; Collection date 2019.
© The Author(s) 2019
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/.
PMC Copyright notice
PMCID: PMC6465266 PMID: 30988286
Abstract
With news pushed to smart phones in real time and social media reactions spreading across the globe in seconds, the public discussion can appear accelerated and temporally fragmented. In longitudinal datasets across various domains, covering multiple decades, we find increasing gradients and shortened periods in the trajectories of how cultural items receive collective attention. Is this the inevitable conclusion of the way information is disseminated and consumed? Our findings support this hypothesis. Using a simple mathematical model of topics competing for finite collective attention, we are able to explain the empirical data remarkably well. Our modeling suggests that the accelerating ups and downs of popular content are driven by increasing production and consumption of content, resulting in a more rapid exhaustion of limited attention resources. In the interplay with competition for novelty, this causes growing turnover rates and individual topics receiving shorter intervals of collective attention.
The impacts of technological development on social sphere lack strong empirical foundation. Here the authors presented quantitative analysis of the phenomenon of social acceleration across a range of digital datasets and found that interest appears in bursts that dissipate on decreasing timescales...