Spotting political social bots in Twitter: a dataset for the 2019 Spanish general election

  1. Pastor-Galindo, Javier 1
  2. Zago, Mattia 1
  3. Nespoli, Pantaleone 1
  4. Lopéz Bernal, Sergio 1
  5. Huertas Celdrán, Alberto 2
  6. Gil Pérez, Manuel 1
  7. Ruipérez-Valiente, José A. 1
  8. Martínez Pérez, Gregorio 1
  9. Gómez Mármol, Félix 1
  1. 1 Universidad de Murcia
    info

    Universidad de Murcia

    Murcia, España

    ROR https://ror.org/03p3aeb86

  2. 2 Waterford Institute of Technology
    info

    Waterford Institute of Technology

    Waterford, Irlanda

    ROR https://ror.org/03ypxwh20

Editor: IEEE DataPort

Año de publicación: 2020

Tipo: Dataset

CC BY 4.0

Resumen

While social media has been proved as an exceptionally useful tool to interact with other people and massively and quickly spread helpful information, its great potential has been ill-intentionally leveraged as well to distort political elections and manipulate constituents. In the paper at hand, we analyzed the presence and behavior of social bots on Twitter in the context of the November 2019 Spanish general election. Throughout our study, we classified involved users as social bots or humans, and examined their interactions from a quantitative (i.e., amount of traffic generated and existing relations) and qualitative (i.e., user's political affinity and sentiment towards the most important parties) perspectives. Results demonstrated that a non-negligible amount of those bots actively participated in the election, supporting each of the five principal political parties. The dataset at hand presents the data collected during the observation period (from October 4th, 2019 to November 11th, 2019). It includes both the anonymized tweets and the users' data.