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FakeNewsNet is a comprehensive fake news benchmark providing full news articles, social context from Twitter, and ground truth labels from fact-checking sites.

What Is FakeNewsNet?

Why FakeNewsNet Matters

Fake news detection requires more than text analysis—propagation patterns, user credibility, and engagement signals provide crucial signals.

<svg viewBox="0 0 368 340" xmlns="http://www.w3.org/2000/svg" style="max-width:100%;height:auto" role="img"><rect x="0" y="0" width="368" height="340" rx="12" fill="#0d1117"/><g font-family="ui-monospace,SFMono-Regular,Menlo,Consolas,&quot;Liberation Mono&quot;,monospace" font-size="14"><text xml:space="preserve" x="20" y="31.7"><tspan fill="#c9d1d9">FakeNewsNet Data Structure:</tspan></text><text xml:space="preserve" x="20" y="50.7"><tspan fill="#6e7681">┌─────────────────────────────────────┐</tspan></text><text xml:space="preserve" x="20" y="69.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">          News Article               </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="88.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">  - Title, body text                 </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="107.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">  - Source domain                    </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="126.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">  - Publish date                     </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="145.7"><tspan fill="#6e7681">├─────────────────────────────────────┤</tspan></text><text xml:space="preserve" x="20" y="164.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">        Social Context               </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="183.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">  - Tweets sharing article           </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="202.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">  - Retweet cascades                 </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="221.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">  - User profiles/followers          </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="240.7"><tspan fill="#6e7681">├─────────────────────────────────────┤</tspan></text><text xml:space="preserve" x="20" y="259.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">        Ground Truth                 </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="278.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">  - Fact-check verdict               </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="297.7"><tspan fill="#6e7681">│</tspan><tspan fill="#c9d1d9">  - Explanation                      </tspan><tspan fill="#6e7681">│</tspan></text><text xml:space="preserve" x="20" y="316.7"><tspan fill="#6e7681">└─────────────────────────────────────┘</tspan></text></g></svg>

Detection Approaches Using FakeNewsNet:

ApproachFeaturesF1 Score
Text onlyArticle content~70%
Social onlyPropagation patterns~75%
Multi-modalText + social + user~85%
fakenewsnetmisinformation benchmarksocial media

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