@inproceedings{64c079cec312499c99468963346f1b52,
title = "An nlp analysis of exaggerated claims in science news",
abstract = "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.",
author = "Yingya Li and Jieke Zhang and Bei Yu",
note = "Publisher Copyright: {\textcopyright} EMNLP 2017.All right reserved.; EMNLP 2017 2nd Workshop on Natural Language Processing Meets Journal., NLPmJ 2017 ; Conference date: 07-09-2017",
year = "2017",
language = "English (US)",
series = "EMNLP 2017 - 2nd Workshop on Natural Language Processing Meets Journalism, NLPmJ 2017 - Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "106--111",
editor = "Octavian Popescu and Carlo Strapparava",
booktitle = "EMNLP 2017 - 2nd Workshop on Natural Language Processing Meets Journalism, NLPmJ 2017 - Proceedings of the Workshop",
address = "United States",
}