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Machine Learning in LINE 
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suspicious? True ”Fake News” 

How ML helps LINE Fact Checker? • Coverage of Verified/Unverified Verified Messages: 300+ Similar Messages : 35k+ Total Messages : 40k/d Near- Duplication Classification 

Near-Duplication - Use Cases Verified Fake Message: • "footage on Captain's Instagram Stories showed them wearing wedding rings on their both hands, which prove s Captain America and Captain Marvel get married in Las Vegas" Query Checked Result Type Captain America and Captain Marvel get married in Las Vegas True Partial The wedding in Las Vegas is hosted by Captain America and Captain Marvel couple True Semantically Ironman and Black Widow get married in Los Angeles False Syntactically 

ML models • An Approximate Nearest Neighbor model: find similar articles using pretrained embeddings • Pre-trained BERT classifier: verify topics • fine-tuned with TODAY articles !"" #, %, & = ()*"+!, #%- ./ & +01"2ℎ4!. !"" = 5)65!"(!""8~: ) 

ML system under hood Predicted Label Training Data Ingestion Scheduling Orchestration Async Execution Model Management Model Deployment Index-based Vector Search (ANN) Serving 

Query Article Near-duplicate Articles Human evaluated results 

Classification of Articles 

How users are influenced? • 46% users recognize the suspicious news • 33% users actively do the fact check • 25% would share the checked results • 10x times of facts checked • 4M+ impression of the checked fact  %  %  % 


 
 

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