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Modelling the Drift of Social Media Posts

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Information Systems and Technologies (WorldCIST 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 802))

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Abstract

We have developed a theory that allows us to accurately characterize information waves in social networks such as Twitter. This theory is an extrapolation of a mathematical theory that studies particle drifts in the acoustic field. We have noticed that each post on Twitter can be considered as a particle, and its radius is the number of followers of the author of the post. Then the number of likes and retweets of this entry can be considered as a drift of this particle. We have found that our hypothesis is correct, and in this interpretation, Twitter posts behave like particles in the acoustic field. In particular, if the author of the entry has no more than 15,000 followers, then this behavior is characterized as a radiative drift in the acoustic field, and if more than 15,000, then as a viscous drift. Based on this behavior of particles (posts on Twitter), we can mathematically reconstruct an appropriate information wave.

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Notes

  1. 1.

    https://www.rdocumentation.org/packages/rtweet/versions/1.0.2, 08.11.22.

  2. 2.

    https://www.rdocumentation.org/packages/rtweet/versions/1.0.2/topics/search_tweets, 09.11.22.

  3. 3.

    https://www.polsatnews.pl/wiadomosc/2022-07-02/wimbledon-iga-swiatek-lost-to-alize-cornet-end-of-an-impressive-winning-series/, 08.11.22.

  4. 4.

    https://www.rmf24.pl/fakty/polska/news-stanislaw-tyszka-odchodzi-z-kukiz-15-trudna-ale-pozytywna-de,nId,6395750#crp_state=1, 09.11.22.

  5. 5.

    https://wiadomosci.wp.pl/po-jej-zniknieciu-ruszyl-child-alert-news-of-5yrs-6831058274978496a, 09.11.22.

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Author information

Authors and Affiliations

  1. Department of Cognitive Science and Mathematical Modelling, University of Information Technology and Management in Rzeszow, Sucharskieho 2, 35-225, Rzeszow, Poland

    Henryka Czyż

  2. University of Information Technology and Management in Rzeszow, Rzeszów, Poland

    Andrew Schumann & Arkadiusz Gaweł

Authors
  1. Henryka Czyż
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  2. Andrew Schumann
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  3. Arkadiusz Gaweł
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Corresponding author

Correspondence to Andrew Schumann .

Editor information

Editors and Affiliations

  1. ISEG, Universidade de Lisboa, Lisbon, Cávado, Portugal

    Alvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania

    Gintautas Dzemyda

  4. DCT, Universidade Portucalense, Porto, Portugal

    Fernando Moreira

  5. TeCIP Institute, Scuola Superiore Sant’Anna, Pisa, Italy

    Valentina Colla

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Czyż, H., Schumann, A., Gaweł, A. (2024). Modelling the Drift of Social Media Posts. In: Rocha, A., Adeli, H., Dzemyda, G., Moreira, F., Colla, V. (eds) Information Systems and Technologies. WorldCIST 2023. Lecture Notes in Networks and Systems, vol 802. Springer, Cham. https://doi.org/10.1007/978-3-031-45651-0_39

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