An NLP Analysis of Exaggerated Claims in Science News

The discrepancy between science and media has been affecting the effectiveness of science communication. Original findings from science publications may be distorted with altered claim strength when reported to the public, causing misinformation spread. This study conducts an NLP analysis of exaggerated claims in science news, and then constructed prediction models for identifying claim strength levels in science reporting. The results demonstrate different writing styles journal articles and news/press releases use for reporting scientific findings. Preliminary prediction models reached promising result with room for further improvement.

• Publication year

  2017

• Venue

  NLPmJ@EMNLP

• Publication date

  Unknown publication date

• Fields of study

  Computer Science

• Identifiers
  DOI 10.18653/v1/W17-4219
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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