Designing for affective warnings & cautions to protect against online misinformation threats

Fiona Carroll, Bastian Bonkel

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)

Abstract

Social media's affordance for misinformation is compromising the glue that holds us and our society together. By influencing and manipulating our human behaviour particularly the decisions we make and opinions we form, it is polarising our existence in not only the virtual but also the physical world in which we live. Yet, despite being aware of the destructive nature of misinformation in general, many of us still don't seem to understand/see the full danger on an individual basis. Hence, as we have witnessed during Covid 19, many people still continue to share this misinformation widely. The authors of this paper feel that there is an urgent need to support people in being more aware of false information whilst online. In this paper, we share thoughts around some of the mechanisms that people currently use to identify misinformation online. In particular, the focus is on a study that explores participant's experiences of ten different visualisation effects on a Facebook page. The findings highlight that some of these initial visualisation designs are more effective than the others in informing people that something is not quite what it should be. Like in the physical world, we propose the design of a set of affective online visual warnings and cautions that we hope can be further developed to fight online misinformation and counter it's current negative influence on society.

Original languageEnglish
Pages116-120
Number of pages5
DOIs
Publication statusPublished - 21 Jul 2021
Event34th British Human Computer Interaction Conference Interaction Conference, BCS HCI 2021 - Virtual, Online
Duration: 19 Jul 202121 Jul 2021

Conference

Conference34th British Human Computer Interaction Conference Interaction Conference, BCS HCI 2021
CityVirtual, Online
Period19/07/2121/07/21

Keywords

  • Affective
  • Awareness
  • Caution
  • Misinformation
  • Perception
  • Visualisation effects
  • Warning

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