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A model for the Twitter sentiment curve

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  • Giacomo Aletti
  • Irene Crimaldi
  • Fabio Saracco

Abstract

Twitter is among the most used online platforms for the political communications, due to the concision of its messages (which is particularly suitable for political slogans) and the quick diffusion of messages. Especially when the argument stimulate the emotionality of users, the content on Twitter is shared with extreme speed and thus studying the tweet sentiment if of utmost importance to predict the evolution of the discussions and the register of the relative narratives. In this article, we present a model able to reproduce the dynamics of the sentiments of tweets related to specific topics and periods and to provide a prediction of the sentiment of the future posts based on the observed past. The model is a recent variant of the Pólya urn, introduced and studied in Aletti and Crimaldi (2019, 2020), which is characterized by a “local” reinforcement, i.e. a reinforcement mechanism mainly based on the most recent observations, and by a random persistent fluctuation of the predictive mean. In particular, this latter feature is capable of capturing the trend fluctuations in the sentiment curve. While the proposed model is extremely general and may be also employed in other contexts, it has been tested on several Twitter data sets and demonstrated greater performances compared to the standard Pólya urn model. Moreover, the different performances on different data sets highlight different emotional sensitivities respect to a public event.

Suggested Citation

  • Giacomo Aletti & Irene Crimaldi & Fabio Saracco, 2021. "A model for the Twitter sentiment curve," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-28, April.
    • Handle: RePEc:plo:pone00:0249634
    DOI: 10.1371/journal.pone.0249634
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    References listed on IDEAS

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    1. Fabiana Zollo & Petra Kralj Novak & Michela Del Vicario & Alessandro Bessi & Igor Mozetič & Antonio Scala & Guido Caldarelli & Walter Quattrociocchi, 2015. "Emotional Dynamics in the Age of Misinformation," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-22, September.
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    1. Giacomo Aletti & Irene Crimaldi, 2021. "The Rescaled Pólya Urn and the Wright—Fisher Process with Mutation," Mathematics, MDPI, vol. 9(22), pages 1-11, November.

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