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Vienna Science and Technology Fund

About the project

In November 2021, we started the project Emotional Misinformation – The Interplay of Emotion and Misinformation Spreading on Social Media (EMOMIS). It is funded by the Vienna Science and Technology Fund (WWTF) for a period of three years and 4 months. What we do in 5 bullet points:

  • We have investigated how emotional state influences discernment between true and false news, and which emotions such news trigger, and what their function in the processing of misinformation is.
  • We investigate the large-scale interplay of emotions around news of different trustworthiness on Twitter from 2020 to 2023.
  • We evaluate ways of measuring misinformation in social media data.
  • We develop novel interventions that consider the social identities our believes and emotions around them are linked to.
  • We simulate the dynamics of emotions around news, and the potential effect of algorithmic interventions on misinformation spreading using Agent Based Modelling.

For more:

  • Summary of project results in April 2024
  • Slides of our first online study on how emotions and fake news recognition are related.
  • Slides of a talk at the Conference on Intelligent Machines, Emotions and the Planet
  • Video of a panel discussion, including a brief introduction to EMOMIS, starting at at 29 minutes into the video.
  • Eine Übersicht zu unserem Projekt auf deutsch, mit vielen anderen spannenden Forschungsergebnissen gibt es hier.

Project talks

Conference and seminar talks



For the general public




  • March-July 2024: Gabija Aurylaite from University of Vienna runs our first large social identity intervention.
  • June-August 2023: Ruggero Lazzaroni from RWTH Aachen did a summer research internship at the CSH, funded by an Erasmus scholraship, to investigate the validity of the NewsGuard news reliability ratings
  • Since September 2023: Adam Urosevic joined us for an internship with Jula Lühring on reconstructing the Austrian Twitter network around political news, in relation to the reliability of news shared.