Unraveling the Origin of Social Bursts in Collective Attention
March 15, 2019 Β· Declared Dead Β· π Scientific Reports
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Manlio De Domenico, Eduardo G. Altmann
arXiv ID
1903.06588
Category
physics.soc-ph
Cross-listed
cond-mat.dis-nn,
cs.SI
Citations
52
Venue
Scientific Reports
Last Checked
5 months ago
Abstract
In the era of social media, every day billions of individuals produce content in socio-technical systems resulting in a deluge of information. However, human attention is a limited resource and it is increasingly challenging to consume the most suitable content for one's interests. In fact, the complex interplay between individual and social activities in social systems overwhelmed by information results in bursty activity of collective attention which are still poorly understood. Here, we tackle this challenge by analyzing the online activity of millions of users in a popular microblogging platform during exceptional events, from NBA Finals to the elections of Pope Francis and the discovery of gravitational waves. We observe extreme fluctuations in collective attention that we are able to characterize and explain by considering the co-occurrence of two fundamental factors: the heterogeneity of social interactions and the preferential attention towards influential users. Our findings demonstrate how combining simple mechanisms provides a route towards complex social phenomena.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β physics.soc-ph
π
π
The Cartographer
R.I.P.
π»
Ghosted
Networks beyond pairwise interactions: structure and dynamics
R.I.P.
π»
Ghosted
Statistical physics of human cooperation
R.I.P.
π»
Ghosted
Vital nodes identification in complex networks
R.I.P.
π»
Ghosted
Influence maximization in complex networks through optimal percolation
R.I.P.
π»
Ghosted
Scale-free networks are rare
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted