Analysing the Existence of Organisation Specific Languages on Twitter: The Dataset

  1. Sánchez-Corcuera, Rubén 1
  2. Zubiaga, Arkaitz 2
  3. Almeida, Aitor 1
  1. 1 Universidad de Deusto
    info

    Universidad de Deusto

    Bilbao, España

    ROR https://ror.org/00ne6sr39

  2. 2 Queen Mary University of London
    info

    Queen Mary University of London

    Londres, Reino Unido

    ROR https://ror.org/026zzn846

Verleger: IEEE DataPort

Datum der Publikation: 2021

Art: Dataset

CC BY 4.0

Zusammenfassung

The presence of organisations in Online Social Networks (OSNs) has motivated malicioususers to look for attack vectors, which are then used to increase the possibility of carrying out successfulattacks and obtaining either private information or access to the organisation. This article hypothesisedthat organisations have specific languages that their members use in OSNs, which malicious users couldpotentially use to carry out an impersonation attack. To prove these specific languages, we propose twotasks: classifying tweets in isolation by their author’s organisation and classifying users’ entire timelines byorganisation. To accomplish both tasks, we generate this dataset of over 15 million tweets from more than 5000 members of five different organisations.