Issue |
EPL
Volume 122, Number 2, April 2018
|
|
---|---|---|
Article Number | 28002 | |
Number of page(s) | 7 | |
Section | Interdisciplinary Physics and Related Areas of Science and Technology | |
DOI | https://doi.org/10.1209/0295-5075/122/28002 | |
Published online | 19 June 2018 |
Analytical study of quality-biased competition dynamics for memes in social media
1 Dipartimento di Fisica, Sapienza Università di Roma - P. le A. Moro 2, I-00185 Roma, Italy
2 Istituto dei Sistemi Complessi (ISC- CNR) - Via dei Taurini 19, I-00185 Roma, Italy
Received: 20 March 2018
Accepted: 22 May 2018
The spreading of news, memes and other pieces of information occurring via online social platforms has a strong and growing impact on our modern societies, with enormous consequences, that may be beneficial but also catastrophic. In this work we consider a recently introduced model for information diffusion in social media taking explicitly into account the competition of a large number of items of diverse quality. We map the meme dynamics onto a one-dimensional diffusion process that we solve analytically, deriving the lifetime and popularity distributions of individual memes. We also present a mean-field type of approach that reproduces the average stationary properties of the dynamics. In this way we understand in detail how the different ingredients of the model (size of users memory, rate of introduction of new memes, intrinsic meme fitness) affect meme spreading at the individual and collective level. This opens the path for the inclusion of additional, more realistic, features, such as heterogeneities in the behavior of individual users.
PACS: 89.65.-s – Social and economic systems / 89.75.Hc – Networks and genealogical trees / 89.20.Hh – World Wide Web, Internet
© EPLA, 2018
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.