Objective
Disinformation is a growing and pervasive problem in modern society. Adolescents spend over 6.5 hours per day on their smartphones and many use social media as a primary information source. There is ample indication in the developmental science literature that adolescents might be particularly susceptible to disinformation. Yet surprisingly little is known about how susceptibility to disinformation changes throughout adolescence and how we might foster youths resilience against disinformation. Here I propose an innovative research program to develop the first comprehensive account of susceptibility to disinformation during adolescence. With this fundamental knowledge, I will develop new instruments to promote truth discernment in youths, which are urgently needed in todays digital era. While many prior developmental studies rely on self-reported online activities, the proposed research will innovate this field by gaining deep and objective insights by applying natural language models to adolescents social media data, computational models of reinforcement learning and decision-making in novel experimental paradigms, and network analyses to capture the interplay between risk factors. This approach will gain novel and necessary insights into: 1. the types of (dis)information that adolescents encounter on social media. 2. How persuasion techniques affect adolescents' veracity judgements and information sharing decisions. 3. The learning processes that underlie social influence and impact adolescents veracity judgements and information sharing decisions. 4. The individual differences which make adolescents more susceptible to disinformation and extreme views. The findings will result in a comprehensive, fundamental understanding of adolescents susceptibility to disinformation, including risk factor contexts, and the first evidence-based educational program against disinformation tailored to youths age specific needs.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsmobile phones
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Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
2311 EZ Leiden
Netherlands