Dr Yunfei Long
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Email
yl20051@essex.ac.uk -
Location
Colchester Campus
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Academic support hours
My Academic Support Hours will be 2-3 pm on Friday via zoom. The zoom link for this is available from my profile on my CE 314/887 course MOODLE page. Please wait in the waiting room until I can admit your account.
Profile
Biography
My research is focused on natural language understanding, mainly text processing (including multimodality processing), user profiling, emotion analysis, and digital mental health.
Qualifications
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PhD The Hong Kong Polytechnic University, (2019)
Research and professional activities
Research interests
Developing novel Natural Language Processing and Graph Representation Learning techniques for modelling health related data
This research aims to develop a series of improvement works for NLP and GRL in clinical data and other health-related data that will provide: 1. Adapt Responsible Research & Innovation (RRI) methods to start the interdisciplinary clinical data science and NLP works in Essex. 2. Prototype a person-centered supervised model training process to refine definitions and expose and explore tacit and latent knowledge in psychotherapy assessment. 3. Identify the key factors contributing to performance and trust in the model pipeline (data, processing, deployment) by examining domain expert requirements for the qualities of an engaging, interactive feedback interface and eliciting broader concerns about its acceptability. 4. Assess whether patient and practitioner knowledge base in developing a digital mental health decision support tool increases performance and trust in it.
Teaching and supervision
Current teaching responsibilities
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Data Structures and Algorithms (CE204)
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Natural Language Engineering (CE314)
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Natural Language Engineering (CE887)
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Information Retrieval (CE306)
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Information Retrieval (CE706)
Publications
Journal articles (20)
Chen, I-H., Long, Y., Lu, Q. and Huang, C-R., (2021). Orthographic features for emotion classification in Chinese in informal short texts. Language Resources and Evaluation. 55 (2), 329-352
Lin, Z., Long, Y., Du, J. and Xu, R., (2021). A Multi-modal Sentiment Recognition Method Based on Multi-task Learning. Beijing Daxue Xuebao (Ziran Kexue Ban)/Acta Scientiarum Naturalium Universitatis Pekinensis. 57 (1), 7-15
Ong, ZX., Dowthwaite, L., Perez Vallejos, E., Rawsthorne, M. and Long, Y., (2021). Measuring Online Wellbeing: A Scoping Review of Subjective Wellbeing Measures. Frontiers in Psychology. 12, 616637-
Xiang, R., Chersoni, E., Lu, Q., Huang, C., Li, W. and Long, Y., (2021). Lexical data augmentation for sentiment analysis. Journal of the Association for Information Science and Technology
Jin, G., Zhou, J., Qu, W., Long, Y. and Gu, Y., (2021). Exploiting Rich Event Representation to Improve Event Causality Recognition. Intelligent Automation & Soft Computing. 29 (3), 161-173
Ito-Jaeger, S., Perez Vallejos, E., Curran, T., Spors, V., Long, Y., Liguori, A., Warwick, M., Wilson, M. and Crawford, P., (2021). Digital video interventions and mental health literacy among young people: a scoping review.. Journal of Mental Health, 1-11
Shen, J., Ma, MD., Xiang, R., Lu, Q., Vallejos, EP., Xu, G., Huang, C-R. and Long, Y., (2020). Dual memory network model for sentiment analysis of review text. Knowledge-Based Systems. 188, 105004-105004
Bergin, AD., Vallejos, EP., Davies, EB., Daley, D., Ford, T., Harold, G., Hetrick, S., Kidner, M., Long, Y., Merry, S., Morriss, R., Sayal, K., Sonuga-Barke, E., Robinson, J., Torous, J. and Hollis, C., (2020). Preventive digital mental health interventions for children and young people: a review of the design and reporting of research. npj Digital Medicine. 3 (1), 133-
Wu, T., Zhou, J., Qu, W., Gu, Y., Li, B., Zhong, H. and Long, Y., (2020). Improving AMR parsing by exploiting the dependency parsing as an auxiliary task. Multimedia Tools and Applications
Wei, T., Qu, W., Zhou, J., Long, Y., Gu, Y. and Xia, Z., (2020). Improving Chinese Word Representation with Conceptual Semantics. Computers, Materials & Continua. 64 (3), 1897-1913
Xiang, R., Lu, Q., Jiao, Y., Zheng, Y., Ying, W. and Long, Y., (2019). Leveraging writing systems changes for deep learning based Chinese affective analysis. International Journal of Machine Learning and Cybernetics. 10 (11), 3313-3325
Long, Y., Xiang, R., Lu, Q., Huang, C-R. and Li, M., (2019). Improving attention model based on cognition grounded data for sentiment analysis. IEEE Transactions on Affective Computing, 1-1
Chen, I-H., Zhao, Q., Long, Y., Lu, Q. and Huang, C-R., (2019). Mandarin Chinese modality exclusivity norms. PLoS One. 14 (2), e0211336-e0211336
Chen, I-H., Long, Y., Lu, Q. and Huang, C-R., (2019). Metaphor Detection: Leveraging Culturally Grounded Eventive Information. IEEE Access. 7, 10987-10998
Zhou, J., Lu, Q., Gui, L., Xu, R., Long, Y. and Wang, H., (2019). MTTFsite: cross-cell type TF binding site prediction by using multi-task learning.. Bioinformatics. 35 (24), 5067-5077
Li, M., Lu, Q., Xiong, D. and Long, Y., (2018). Phrase embedding learning based on external and internal context with compositionality constraint. Knowledge-Based Systems. 152, 107-116
Zhao, Q., Huang, C-R. and Long, Y., (2018). Synaesthesia in Chinese: A corpus-based study on gustatory adjectives in Mandarin. Linguistics. 56 (5), 1167-1194
Long, Y., Xiang, R., Lu, Q., Xiong, D., Huang, C-R., Bi, C. and Li, M., (2018). Learning Heterogeneous Network Embedding From Text and Links. IEEE Access. 6, 55850-55860
Li, M., Lu, Q., Long, Y. and Gui, L., (2017). Inferring Affective Meanings of Words from Word Embedding. IEEE Transactions on Affective Computing. 8 (4), 443-456
Gu, Y., Wang, D., Wang, Y., Long, Y., Jiang, S., Zhou, J. and Qu, W., (2016). Similar spatial textual objects retrieval strategy. Beijing Daxue Xuebao (Ziran Kexue Ban)/Acta Scientiarum Naturalium Universitatis Pekinensis. 52 (1), 120-126
Conferences (18)
Long, Y., Xu, H., Qi, P., Zhang, L. and Li, J., (2021). Graph Attention Network for Word Embeddings
Xiang, R., Chersoni, E., Long, Y., Lu, Q. and Huang, C-R., (2020). Lexical Data Augmentation for Text Classification in Deep Learning
Zhao, Q., Long, Y. and Huang, C-R., (2020). Linguistic Synaesthesia of Mandarin Sensory Adjectives: Corpus-Based and Experimental Approaches
Xiang, R., Gao, X., Long, Y., Li, A., Chersoni, E., Lu, Q. and Huang, C-R., (2020). Ciron: a New Benchmark Dataset for Chinese Irony Detection
Xiang, R., Long, Y., Wan, M., Gu, J., Lu, Q. and Huang, C-R., (2020). Affection Driven Neural Networks for Sentiment Analysis
Zhong, H., Zhou, J., Qu, W., Long, Y. and Gu, Y., (2020). An Element-aware Multi-representation Model for Law Article Prediction
Klyueva, N., Long, Y., Huang, CR. and Lu, Q., (2018). Food-related sentiment analysis for Cantonese
Long, Y., (2017). Fake News Detection Through Multi-Perspective Speaker Profiles
Chen, I-H., Long, Y., Lu, Q. and Huang, C-R., (2017). Leveraging Eventive Information for Better Metaphor Detection and Classification
Long, Y., Qin, L., Xiang, R., Li, M. and Huang, C-R., (2017). A Cognition Based Attention Model for Sentiment Analysis
Li, M., Lu, Q. and Long, Y., (2017). Representation Learning of Multiword Expressions with Compositionality Constraint
Li, M., Long, Y., Lu, Q. and Li, W., (2016). Emotion corpus construction based on selection from hashtags
Li, M., Long, Y. and Lu, Q., (2016). A regression approach to valence-arousal ratings of words from word embedding
Li, M., Wang, D., Lu, Q. and Long, Y., (2016). Event based emotion classification for news articles
Long, Y., Lu, Q., Xiao, Y., Li, M. and Huang, C-R., (2016). Domain-specific user preference prediction based on multiple user activities
Long, Y., Xiong, D., Lu, Q., Li, M. and Huang, C-R., (2016). Named Entity Recognition for Chinese Novels in the Ming-Qing Dynasties
Li, M., Lu, Q., Gui, L. and Long, Y., (2016). Towards Scalable Emotion Classification in Microblog Based on Noisy Training Data
Li, B., Long, Y. and Qu, W., (2015). Dependency parsing for Chinese long sentence: A second-stage main structure parsing method
Grants and funding
2020
ExTRA-PPOLATE (Explainable Therapy Related Annotations: Patient & Practitioner Oriented Learning Assisting Trust & Engagement)
Engineering and Physical Sciences Research Council
2019
Mondaq KTP 2
Innovate UK (formerly Technology Strategy Board)
Contact
Academic support hours:
My Academic Support Hours will be 2-3 pm on Friday via zoom. The zoom link for this is available from my profile on my CE 314/887 course MOODLE page. Please wait in the waiting room until I can admit your account.