Dr Xingyi Song
Department of Computer Science
Academic Fellow in Computational Media Analysis, Natural Language Processing
Member of the Natural Language Processing research group
+44 114 222 1867
Full contact details
Department of Computer Science
Regent Court (DCS)
Dr Xingyi Song, an Academic Fellow at the Department of Computer Science, University of Sheffield, UK. He is a member of the Natural Language Processing group and GATE team (https://gate.ac.uk/)
Previously he worked as a machine translation specialist at Iconic Translation Machine (2015-2016) and Research Associate for several EU funded projects such as Kconnect, Knowmak and Risis2 (from 2016-2021)) at the University of Sheffield.
He completed his MSc and PhD in Natural Language Processing group at the University of Sheffield. His research interests are in Natural Language Processing, Computational Social Science, sentiment analysis and Bio-medical text processing.
- An exploratory study on utilising the web of linked data for product data mining. SN Computer Science, 4(1). View this article in WRRO
- Text mining occupations from the mental health electronic health record: A natural language processing approach using records from the Clinical Record Interactive Search (CRIS) platform in south London, UK. BMJ Open, 11(3).
- Using ontologies to map between research data and policymakers’ presumptions: the experience of the KNOWMAK project. Scientometrics. View this article in WRRO
- A Python script for adaptive layout optimization of trusses. Structural and Multidisciplinary Optimization. View this article in WRRO
- CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital. BMC Medical Informatics and Decision Making, 18. View this article in WRRO
- Classification aware neural topic model for COVID-19 disinformation categorisation. PLOS ONE, 16(2), e0247086-e0247086.
Conference proceedings papers
- Comparative Analysis of Engagement, Themes, and Causality of Ukraine-Related Debunks and Disinformation (pp 128-143)
- Comparing topic-aware neural networks for bias detection of news. Proceedings of 24th European Conference on Artificial Intelligence (ECAI 2020), Vol. 325 (pp 2054-2061). Santiago de Compostela, Spain, 29 August 2020 - 2 September 2020. View this article in WRRO
- Using deep neural networks with intra- And inter-sentence context to classify suicidal behaviour. LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings (pp 1303-1310)
- View this article in WRRO RP-DNN: A tweet level propagation context based deep neural networks for early rumor detection in social media. LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings (pp 6094-6105)
- 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, June 2019 - June 2019.
- View this article in WRRO 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. Minneapolis, Minnesota, USA, 6 June 2019 - 7 June 2019.
- A deep neural network sentence level classification method with context information. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (pp 900-904). Brussels, Belgium, 31 October 2018 - 4 November 2018. View this article in WRRO
- 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, September 2017 - September 2017.
- Sheffield Systems for the English-Romanian WMT Translation Task. Proceedings of the First Conference on Machine Translation
- Data selection for discriminative training in statistical machine translation. Proceedings of the 17th Annual Conference of the European Association for Machine Translation, EAMT 2014 (pp 45-52)
- BLEU deconstructed: Designing a Better MT Evaluation Metric. Proceedings of the 14th International Conference on Intelligent Text Processing and Computational Linguistics (CICLING)
- Regression and Ranking based Optimisation for Sentence Level Machine Translation Evaluation. Proceedings of the Sixth Workshop on Statistical Machine Translation. Edinburgh, UK