Scaling in words on Twitter

Eszter Bokányi, Dániel Kondor, Gábor Vattay

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Scaling properties of language are a useful tool for understanding generative processes in texts. We investigate the scaling relations in citywise Twitter corpora coming from the metropolitan and micropolitan statistical areas of the United States. We observe a slightly superlinear urban scaling with the city population for the total volume of the tweets and words created in a city. We then find that a certain core vocabulary follows the scaling relationship of that of the bulk text, but most words are sensitive to city size, exhibiting a super- or a sublinear urban scaling. For both regimes, we can offer a plausible explanation based on the meaning of the words. We also show that the parameters for Zipf’s Law and Heaps’ Law differ on Twitter from that of other texts, and that the exponent of Zipf’s Law changes with city size.

Original languageEnglish
Article number190027
JournalRoyal Society Open Science
Volume6
Issue number10
DOIs
Publication statusPublished - Jan 1 2019

Keywords

  • Linguistic laws
  • Twitter
  • Urban scaling

ASJC Scopus subject areas

  • General

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