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Computational Journalism

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Computational Journalism

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Research Frontiers in Natural Language Processing for News Extraction

Development of NLP pipelines that automatically identify, classify, and extract structured news elements from unstructured text sources.

Semantic Drift in Real-time News Narratives
Implicit Bias Detection Across Global News Corpora
Temporal Coherence in Multi-source Fact Extraction
Narrative Attribution Without Bylines or Metadata
Event Coreference Across Languages and Dialects
Sarcasm and Irony in Breaking News Detection
Source Reliability Estimation from Linguistic Patterns
Context Collapse in Automated News Summarization
Disinformation Signal Propagation at Document Scale
Stance Evolution Tracking in Developing Stories

All Computational Journalism PhD categories