Origin of the log-normal popularity distribution of trending memes in social networks.

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ID: 102311
2020
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Abstract
We study the origin of the log-normal popularity distribution of trending memes observed in many real social networks. Based on a biological analogy, we introduce a fitness of each meme, which is a natural assumption based on sociological reasons. From numerical simulations, we find that the relative popularity distribution of the trending memes becomes a log-normal distribution when the fitness of the meme increases exponentially. On the other hand, if the fitness grows slowly, then the distribution significantly deviates from the log-normal distribution. This indicates that the fast growth of fitness is the necessary condition for the trending meme. Furthermore, we also show that the popularity of the trending topic grows linearly. These results provide a clue to understand long-lasting questions, such as what causes some memes to become extremely popular and how such memes are exposed to the public much longer than others.
Reference Key
yook2020originphysical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Yook, Soon-Hyung;Kim, Yup;
Journal physical review e
Year 2020
DOI
10.1103/PhysRevE.101.012312
URL
Keywords
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