Evaluating the influence of the reporting of natural disasters on public understanding of their causes and possible prevention solutions

Grantham Scholar Ye Jiang’s is now at Qingdao University of Science and Technology as an Associate Professor. Ye’s project at the Grantham Centre investigated correlations between natural disasters, climate change, and the reporting and understanding of such events.  

The project

This project will investigate correlations between natural disasters, climate change, and the reporting and understanding of such events. It will deploy a Natural Language Processing (NLP) framework for text analysis, used to understand the content of news articles and messages on social media, and methods from journalism and machine learning strategy to examine the ways in which news stories are reported which generate emotions or sentiments polarity by using the language of risk, fear and anxiety.

Examination of the style and content of news stories will establish the degree to which framing of information (amplifying, diminishing or distorting the event) has been undertaken. An open-source NLP software, GATE, will be applied in this project for analysing the news articles from different types of sources, and investigating the use of language in the articles. The latest word-embedding will also be applied for analysing the similarity between words, sentences and documents. News articles will be classified according to sentiment and emotion, to understand what attitudes and motivations appear in different places and time periods.


Ye Jiang was part of a team that won the Hyperpartisan News Detection Challenges. Find out more about the competition and the winning team.

If you want to keep up to date with Ye Jiang’s work, then you can go to his website.


Xingyi Song, Johann Petrak, Ye Jiang, Iknoor Singh, Diana Maynard, and Kalina Bontcheva. “Classification aware neural topic model for COVID-19 disinformation categorisation.” Plos one 16, no. 2, 2021. PDF

Jiajia Liu, Yimin Wang, Xin Huang, Marianna Korsos, Ye Jiang, Yuming Wang, Robert Erd´elyi. Reliability of AI-generated magnetograms from only EUV images. Nature Astronomy, 2021. PDF
Ye Jiang. “Detecting Journalistic Framing and Attitudes on News Reporting about Climate Change.” PhD diss., University of Sheffield, 2020. PDF

Ye Jiang, Yimin Wang, Xingyi Song, Diana Maynard. Comparing topic-aware neural networks for bias detection of news. Proceeding of ECAI 2020. PDF

Yimin Wang, Jiajia Liu, Ye Jiang, and Robert Erdélyi. CME Arrival Time Prediction Using Convolutional Neural Network. The Astrophysical Journal, 2019. 881(1): 15. PDF

Ye Jiang, Johann Petrak, Xingyi Song, Kalina Bontcheva, and Diana Maynard. Team Bertha von Suttner at SemEval-2019 Task 4: Hyperpartisan News Detection using ELMo Sentence Representation Convolutional Network. Proceedings of the 13th International Workshop on Semantic Evaluation, 2019. PDF

Ye Jiang, Xingyi Song, Jackie Harrison, Shaun Quegan, and Diana Maynard.Comparing Attitudes to Climate Change in the Media using sentiment analysis based on Latent Dirichlet Allocation. Proceedings of the 2017 EMNLP Workshop: Natural Language Processing meets Journalism, 2017. PDF

Hong Xu, Ye Jiang, Yimin Wang, Yewei Sun, Xueqing Li. Sentence length, sentence fragment and images affecting presentation of search result pages. Proceedings of the 2015 JIMET Conference, 2015. PDF

Social media

You can find Ye Jiang on LinkedIn.


Dr Diana Maynard

Department of Computer Science


Professor Shaun Quegan

School of Mathematics and Statistics