ORCID Profile
0000-0002-2375-0539
Current Organisation
University of North Dakota
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Publisher: AIP Publishing
Date: 06-2020
DOI: 10.1063/5.0004983
Abstract: In this paper, we quantify the statistical properties and dynamics of the frequency of hashtag use on Twitter. Hashtags are special words used in social media to attract attention and to organize content. Looking at the collection of all hashtags used in a period of time, we identify the scaling laws underpinning the hashtag frequency distribution (Zipf’s law), the number of unique hashtags as a function of s le size (Heaps’ law), and the fluctuations around expected values (Taylor’s law). While these scaling laws appear to be universal, in the sense that similar exponents are observed irrespective of when the s le is gathered, the volume and the nature of the hashtags depend strongly on time, with the appearance of bursts at the minute scale, fat-tailed noise, and long-range correlations. We quantify this dynamics by computing the Jensen–Shannon ergence between hashtag distributions obtained τ times apart and we find that the speed of change decays roughly as 1/τ. Our findings are based on the analysis of 3.5×109 hashtags used between 2015 and 2016.
Location: Germany
Location: Germany
Location: No location found
No related grants have been discovered for Diego Fregolent Mendes de Oliveira.