Sources

Here you will find all the sources this chapter on media literacy and source criticism draws on, organized by topic.

Methods and concepts

• 🇬🇧 Mike Caulfield: SIFT (The Four Moves). The original post in which Caulfield introduces the four steps of the SIFT method, the basis of the verification process covered in this chapter.
• 🇬🇧 Wineburg & McGrew: Lateral Reading and the Nature of Expertise (Teachers College Record, 2019). The academic study showing that professional fact-checkers judge faster and more reliably through lateral reading than experts who examine a page from the inside.
• 🇬🇧 UNESCO: Media and Information Literacy. The official UNESCO page on the MIL concept, which brings together media and information literacy and provides the framework for this chapter.
• 🇬🇧 SBCC Library: SIFT & PICK. A library guide that combines the SIFT verification method with the PICK selection aid, showing how to both evaluate and appropriately choose sources.
• 🇬🇧 Meriam Library, CSU Chico: CRAAP Test. The source of the well-known CRAAP test, a checklist for assessing the credibility of a source (Currency, Relevance, Authority, Accuracy, Purpose).
• 🇬🇧 Saint Mary's University: SIFT Method (PDF). A compact one-page summary of the SIFT method as a handout, handy for printing and taking along.

Disinformation and research

• 🇬🇧 Wardle & Derakhshan: Information Disorder (Council of Europe, 2017, PDF). The foundational report that coined the distinction between mis-, dis- and malinformation used in this chapter.
• 🇬🇧 Reuters Institute: Echo chambers, filter bubbles and polarisation: a literature review. A research overview that summarizes the empirical state of knowledge on echo chambers and filter bubbles and shows why these claims are weaker than often assumed.
• 🇬🇧 Reuters Institute: The truth behind filter bubbles: Bursting some myths. An accessible write-up of this research that dispels widespread myths about filter bubbles.
• 🇬🇧 Eli Pariser: Beware online filter bubbles (TED Talk). The popular talk that made the term "filter bubble" widely known, included here as the historical starting point of the debate.
• 🇬🇧 Milli et al.: Engagement, user satisfaction, and the amplification of divisive content (PNAS Nexus, 2025). A recent study showing how algorithms amplify divisive content by optimizing for engagement.
• 🇬🇧 EUvsDisinfo (EEAS): euvsdisinfo.eu. The database of the European External Action Service, which documents and exposes targeted (often state-run) disinformation campaigns.

AI fakes

• 🇬🇧 News Literacy Project: RumorGuard / The 5 factors. A guide with five factors for quickly assessing the credibility of an online claim.
• 🇬🇧 NPR: Fake viral images of an explosion at the Pentagon were probably created by AI. Reporting on an AI-generated fake image that serves as a concrete case study for deepfakes in this chapter.
• 🇬🇧 Al Jazeera: Fake Pentagon explosion photo goes viral: How to spot an AI image. A second write-up of the same case that also gives practical hints on how to recognize AI images.

Fact-checking and tools

• 🇬🇧 IFCN: Code of Principles / The Commitments. The code of conduct of the International Fact-Checking Network, by which you can recognize reputable, independent fact-checkers.
• 🇩🇪 CORRECTIV: Faktencheck. The fact-checking section of a well-known German investigative center, a central point of reference for verified claims in the German-speaking world.
• 🇩🇪 ARD: Faktenfinder (Tagesschau). The fact-checking service of Tagesschau, which verifies false reports currently in circulation.
• 🇬🇧 EUfactcheck: Flowchart. A flowchart that visualizes the fact-checking process step by step.
• 🇬🇧 ❤️ CIVIX: Ctrl-F: Find the Facts. A free learning program that trains lateral reading and quick online verification.
• 🇬🇧 InVID/WeVerify: Verification Plugin. A free browser tool for verifying images and videos, for example via reverse image search and metadata analysis.
• 🇩🇪 CORRECTIV/GADMO: Geolocation: 5 Tipps, um den Aufnahmeort eines Bilds zu finden. A practical guide on how to determine the actual location where a photo was taken from features in the image.

Wikipedia

• 🇩🇪 Wikipedia:Belege. The guideline requiring Wikipedia to back up statements with reliable sources; it explains why the references lead you to the primary sources.
• 🇩🇪 Wikipedia:Gesichtete Versionen. The explanation of the flagged-revisions system, which describes how Wikipedia catches obvious vandalism before it is displayed.
• 🇬🇧 Reliability of Wikipedia (with Nature study 2005). An overview article on the reliability of Wikipedia that, drawing on the well-known Nature study, shows that Wikipedia is a good starting point but not an end point.

Further learning materials

• 🇬🇧 Mike Caulfield: Web Literacy for Student Fact-Checkers. This book teaches how to use the internet as a fact-checking machine and is written by a well-known expert in MIL. It is also where we find the SIFT method.
• 🇬🇧 Introduction to College Research: Disinformation & Fact-Checking. A very good online book on media literacy and source criticism (information literacy skills) with an open license (OER, CC-BY).
• 🇩🇪 European Journalism Observatory. A journalism trade portal that presents media research and industry trends in an accessible way and offers a look behind the scenes of news coverage.