Topic and Emotion Development among Dutch COVID-19 Twitter Communities in the early Pandemic

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The paper focuses on a large collection of Dutch tweets from the Netherlands to get an insight into the perception and reactions of users during the early months of the COVID-19 pandemic. We focused on five major user communities of users: government and health organizations, news media, politicians, the general public and conspiracy theory supporters, investigating differences among them in topic dominance and the expressions of emotions. Through topic modeling we monitor the evolution of the conversation about COVID-19 among these communities. Our results indicate that the national focus on COVID-19 shifted from the virus itself to its impact on the economy between February and April. Surprisingly, the overall emotional public response appears to be substantially positive and expressing trust, although differences can be observed in specific group of users.
Original languageEnglish
Title of host publicationProceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media
EditorsMalvina Nissim, Viviana Patti, Barbara Plank, Esin Durmus
PublisherAssociation for Computational Linguistics (ACL)
Number of pages12
Publication statusPublished - 2020
EventPEOPLES 2020: Workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media - Online, Barcelona, Spain
Duration: 13-Dec-2020 → …
Conference number: 3


WorkshopPEOPLES 2020
Period13/12/2020 → …


  • emotion detection
  • COVID-19
  • Dutch
  • social media analysis
  • NLP

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