I am a Ph.D student supervised by Dr.Diana Maynard at the GATE NLP group Department of Computer Science University of Sheffield. I am also a Grantham Scholar at the Grantham Centre for Sustainable Futures.
My research interests lie in many NLP research topics, including machine learning approaches for text classification, topic modelling and representation learning.
- Address: Room G30, Department of Computer Science, Regent Court, 211 Portobello, Sheffield, S1 4DP, UK.
- Email: yjiang18 (AT) sheffield.ac.uk
- 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
- EUvsVirus: Team WeVerify Detecting Covid-19 Online Disinformation This is the code of several models, includes RNN with attention, CNN with BatchNorm, and HAN (Hierarchical Attention Network) for detecting Covid-19 disinformation on the EUvsVirus, this is a multiclass (11 categories) classification, and used BERT to generate word level embedding.
- Topic-Aware Hierarchical Document Representation for News Biased Detection A Keras implementation of the Hierarchical Attention Network (Yang et al, 2016) incorporating with LDA topic distributions.
- Semantic Evaluation 2019, Task 4: Hyperpartisan News Detection. This is the code for the SemEval 2019 Task 4, Hyperpartisan News Detection submitted by team Bertha von Suttner. The model created with this was the winning entry, see the public leaderboard.