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Entropy in Network Community as an Indicator of Language Structure in Emoji Usage: A Twitter Study Across Various Thematic Datasets

  • Ryan Hartman
  • S. M. Mahdi Seyednezhad
  • Diego Pinheiro
  • Josemar Faustino
  • Ronaldo Menezes
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 812)

Abstract

Emojis are emerging as an alternative way to interact and communicate online, and their large-scale adoption has the potential to reveal distinct patterns of human communication and social interactions. In this work, we investigate the hypothesis that emojis are a kind of language. By building networks of emoji co-occurrence, we examine the diversity of the community structure of such networks with regards to predefined categories of emojis. Using four different techniques of community detection, we validate our hypothesis on six Twitter datasets: five from specific topics and one random dataset. Our results demonstrate that the community structure of emojis is more diverse when they are used in non-random topics such as politics and sports, and that Stochastic Block Models appears to extract communities with higher diversity.

Notes

Acknowledgements

Diego Pinheiro and Josemar Faustino would like to thank the Science Without Borders program (CAPES, Brazil) for financial support under grants 0624/14-4 and 1043-14-5, respectively. This material is based upon work supported by the National Science Foundation under Grant No. CNS 09-23050.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ryan Hartman
    • 1
  • S. M. Mahdi Seyednezhad
    • 1
  • Diego Pinheiro
    • 2
  • Josemar Faustino
    • 1
  • Ronaldo Menezes
    • 3
  1. 1.Department of Computer Engineering and SciencesFlorida Institute of TechnologyMelbourneUSA
  2. 2.Department of Internal MedicineUniversity of CaliforniaDavisUSA
  3. 3.BioComplex Laboratory, Department of Computer ScienceUniversity of ExeterExeterUK

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