Comparing the Decay of Physical and Digital Inoculation Against Disinformation

Henderson, Niklas (2022) Comparing the Decay of Physical and Digital Inoculation Against Disinformation. In: 2022 Defence and Security Doctoral Symposium, 2022-11-09 - 2022-11-10, Cranfield University.

Full text not available from this repository. (Request a copy)

Abstract

Since entering the post-truth digital age, awareness in false information spreading online has increased rapidly. Despite this increased awareness it remains a serious problem, with Russian and Chinese state disinformation campaigns proving effective on online social networks (OSNs), impacting the wider UK political landscape. There are many areas of intervention across the mis- and disinformation landscape, including machine learning detection and classification methods, bad actor research, and some cognitive approaches. One cognitive-based approach is Inoculation Theory, originally developed by William J. McGuire. Inoculation theory follows the biological analogy, in that to increase resistance to persuasion the subject should be pre-exposed to a weakened version of a persuasive argument. Researchers have used inoculation theory in both physical and digital interventions, with participants yielding positive results identifying false information, and resisting “fake news.” This research focuses on understanding how the decay of inoculating effects differs relative to whether the inoculation intervention was delivered digitally or physically. Participants are inoculated to build resistance to disinformation using a board game, and results are compared to the inoculation decay of other, digital disinformation games.

Item Type: Conference or Workshop Item (Poster)
Faculty \ School: Faculty of Science > School of Computing Sciences
Depositing User: LivePure Connector
Date Deposited: 15 Dec 2022 01:11
Last Modified: 04 Mar 2024 16:34
URI: https://ueaeprints.uea.ac.uk/id/eprint/90036
DOI: 10.17862/CRANFIELD.RD.C.6172720.V5

Actions (login required)

View Item View Item