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Tweet topics and sentiments relating to distance learning among Italian Twitter users.

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Public opinion on distance learning in Italy showed a majority of negative sentiments initially, shifting over time. Key concerns included support, application, and anxiety over restrictions, with future use remaining a worry.

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Area of Science:

  • Social Sciences
  • Communication Studies
  • Education Technology

Background:

  • The COVID-19 pandemic necessitated a rapid transition from in-person to distance learning globally.
  • Twitter microblogging data offers a real-time platform for tracking public sentiment on educational shifts.

Purpose of the Study:

  • To analyze public sentiment and evolving topics related to distance learning in Italy between March 2020 and November 2021.
  • To understand the emotional landscape and thematic concerns associated with remote education during the pandemic.

Main Methods:

  • Utilized a two-step sentiment analysis employing VADER and the syuzhet package to gauge overall sentiment and emotions.
  • Applied a dynamic latent Dirichlet allocation (DLDA) model to identify and track key topics in tweets over time.

Main Results:

  • A slight majority of negative opinions were observed, with sentiment trends reversing during the study period.
  • 'Trust' emerged as the most positive emotion, while 'fear' and 'sadness' were the most prevalent negative emotions.
  • Identified key topics: requests for support, concerns about distance learning application, and anxiety over government restrictions; topic 2 gained prominence later.

Conclusions:

  • Public sentiment towards distance learning in Italy evolved, with initial concerns about support and restrictions giving way to future application worries.
  • Despite the end of immediate mandates, a persistent concern exists regarding the potential reintroduction of distance learning in future emergencies.