Toolbox — For Training and Youth Work
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Exercise
Unfake Social Media - Lateral Reading Games - Game 2 - Feed Filter
A fast-paced card-based simulation where players judge whether social-media posts are factual, misleading, or fake, sharpening quick lateral-reading skills.
Aims of the tool
To strengthen credibility assessment by:
a) Training players to evaluate posts quickly using context, clues, and reasoning;
b) Encouraging them to justify decisions and reflect on what makes information reliable or deceptive.
Description of the tool
Developed under the Unfake Social Media project’s Lateral Reading category, Feed Filter: Fact or Fiction places players inside a simulated social-media feed filled with headlines, posts, tweets, and images — some accurate, others misleading or fabricated.
Players must sift through the feed, decide whether each card is reliable or deceptive, and explain their reasoning. The rapid decision-making mirrors real online scrolling behaviour, where credibility judgements are often made instantly.
The game encourages discussion, comparison, and critical thinking, helping players build healthy scepticism and stronger lateral-reading habits.
Available downloads:
Disclaimer
SALTO cannot be held responsible for the inappropriate use of these training tools. Always adapt training tools to your aims, context, target group and to your own skills! These tools have been used in a variety of formats and situations. Please notify SALTO should you know about the origin of or copyright on this tool.
Tool overview
http://toolbox.salto-youth.net/5224
This tool is for
Designed for young people and youth workers, especially in sessions on source evaluation, misinformation, and social-media literacy.
and addresses
Youth Initiatives
It is recommended for use in:
Transnational Youth Initiatives
Materials needed:
Feed Filter Game PDF
Duration:
30-45 minutes
Behind the tool
The tool was created by
Unfake Social Media Erasmus+ KA21
in the context of
Unfake Social Media Erasmus+ KA21
The tool was published to the Toolbox by
GV Vadivan (on 27 November 2025)
and last modified
17 November 2025
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