Jasy Liew Suet Yan, Dr.
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Senior LecturerEmail :
This email address is being protected from spambots. You need JavaScript enabled to view it. Tel : +604 653 4639
Fax : +604 653 3335
Room : 726
School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Pulau PinangResearch Cluster
Data To Knowledge
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Research InterestSentiment Analysis, Natural Language Processing, Computational Linguistics, Text Mining, Social Media Analytics and Visualization, Machine Learning, Affective Computing, Artificial Intelligence, Human Computer Interaction, Information Science and Technology
Specialization
Textual Emotion Detection, Sentiment Analysis, Text Mining, Machine Learning, Natural Language Processing, Content Analysis, Web and Social Media Mining
Qualifications
BSc (Hons.), School of Computer Sciences, USM, Malaysia
MSc, School of Information Studies, SYRACUSE UNIVERSITY, USA
PhD, School of Information Studies, SYRACUSE UNIVERSITY, USA
Interests
My main research goals focus on:
1) Developing computational models that can harnessing textual emotion signals to gain better insights on how people think and behave
2) Developing more emotion-sensitive systems to improve human-computer interactions
Projects of interest include but not limited to: emotion detection and classification from social media text and content, sentiment analysis on consumer reviews, aspect-based sentiment analysis, developing machine learning and deep learning models for natural language processing and understanding, cryptocurrency price prediction using sentiment analysis, mental health detection and monitoring through social media, cyberbullying detection
Projects
Research Grants - PI
2020-2023: Ministry of Higher Education Transdiciplinary Research Grant Scheme (TRGS) (Primary Investigator). Project Title: A Two-pronged Approach in Drawing the Connection between Cyberbullying and Suicide among Adolescents in Malaysia. Co-researchers: Dr. Gan Keng Hoon, Dr. Noor Farizah Ibrahim, Dr. Azriani Ab Rahman, Dr. Asrenee Ab Razak, Dr. Tang Ying.
2020-2023: Ministry of Higher Education Fundamental Research Grant Scheme (FRGS) (Primary Investigator). Project Title: Enhancing Deep Learning Models using Weighted Greedy Algorithm for Cross-Domain Sentiment Classification of Product Reviews. Co-researchers: Dr. Cheah Yu-N, Dr. Lu Xiao.
2018-2021: L'Oréal-UNESCO for Women in Science National Fellowship 2017 (Primary Investigator). Project Title: Sad No More: Building Emotion Sensitive Systems to Detect and Prevent Depression.
2018-2021: USM Short Term Grant (Primary Investigator). Project Title: Exploring Syntactic and Semantic Features for Fine-Grained Emotion Detection in Text. Co-researchers: Dr. Rosni Abdullah & Dr. Nor Athiyah Abdullah.
Research Grants - Co-Researcher
2020-2023: USM Short Term Grant (Co-researcher). Project Title: Development of an Mhealth Application for Video-observed Therapy (VOT) as an Alternative Treatment Monitoring of Tuberculosis Treatment in Kelantan. PI: Dr. Mohd Jazman Che Rahim.
2020-2022: USM Short Term Grant (Co-researcher). Project Title: Integrating Image Processing and Machine Learning to Identify Handwriting Features Useful for Automatic Screening of Autism Spectrum Disorder (ASD) among Children. PI: Dr. Nur Intan Raihana Ruhaiyem.
2017-2019: Research University Individual (RUI) Grant (Co-researcher). Project Title: Detection of user Opinion and Emotion in Online Product Reviews. PI: Dr. Cheah Yu-N.
Community Engagement
2019-Ongoing: Girls2Code: Girls in ICT Campaign (Project Leader). Task Force: Dr. Teh Je Sen, Dr. Azleena Mohd Kassim, Dr. Nor Athiyah Abdullah, Dr. Rosni Abdullah, Mr. Kee Chong Wei. Collaborator: Telebort.
Publications
2021
Liew, J. S. Y., & Turtle, H. R. (2021). Fine-grained emotion classification: Class imbalance effects on classifier performance. In Proceedings of the 2021 IEEE International Conference on Computer Information Sciences (ICCOINS), 74–79. [URL]
Lee, T. R., Teh, J. S., Jamil, N., Yan, J. L. S., & Chen, J. (2021). Lightweight block cipher security evaluation based on machine learning classifiers and active S-boxes. IEEE Access, 9, 134052–134064. [URL]
Idris, M. F., Teh, J. S., Liew, J. S. Y., & Yeoh, W.-Z. (2021). A deep learning approach for active S-box prediction of lightweight generalized Feistel block ciphers. IEEE Access, 9, 104205–104216. [URL]
2020
Liew, J. S. Y., Teh, J. S., Kassim, A. M., Kee, C. W., & Abdullah, R. (2020). Girls2Code: Cultivating interest in programming among young girls in Malaysia by making drawings come to life. Science, Technology, Engineering and Mathematics Education for Girls and Women in Asia-Pacific. UNESCO. [URL]
Yong, K. S., & Liew, J. S. Y. (2020). A text augmentation approach using similarity measures based on neural sentence embeddings for emotion classification on microblogs. In Proceedings of the 2020 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET 2020). DOI: 10.1109/IICAIET49801.2020.9257826. [URL]
Gupta, A., Liew, J. S. Y., & Cheah, Y.-N. (2020). Going big and deep: Using convolutional neural network to leverage training data from multiple domains for cross-domain sentiment classification on product reviews. In Proceedings of the 2020 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET 2020). DOI: 10.1109/IICAIET49801.2020.9257815. [URL]
Lee, T. R., Teh, J. S., Liew, J. S. Y., Jamil, N., & Yeoh, W. Z. (2020). A machine learning approach to predicting block cipher security. In Proceedings of the 7th International Cryptology and Information Security Conference 2020, 122–132. [URL]
2019
Liew, J. S. Y., & Turtle, H. R. (2019). Effect of sampling strategies on fine-grained emotion classification in microblog text. In Proceedings of the IEEE International Conference on Artificial Intelligence and Data Sciences (AiDAS2019). Ipoh, Perak, Malaysia. DOI: 10.1109/AiDAS47888.2019.8970953. [URL]
2017
Liew, J. S. Y., & Zhang, P. (2017). Affect in the ICT Context. In Galliers, R. D., & Stein, M. K. (Eds.), The Routledge Companion to Management Information System (pp. 166-182). DOI: 10.4324/9781315619361. [URL]
2016
Liew, J. S. Y., & Turtle, H. R. (2016). Exposing a set of fine-grained emotion categories from tweets. In Proceedings of the IJCAI 2016 4th Workshop on Sentiment Analysis where AI meets Psychology (SAAIP 2016) (pp. 8–14). New York City, New York, USA. [URL]
Liew, J. S. Y., & Turtle, H. R. (2016). Exploring fine-grained emotion detection in tweets. In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) (pp. 73–80). San Diego, California, USA. DOI: 10.18653/v1/N16-2011. [URL]
Liew, J. S. Y., & Turtle, H. R. (2016). EmoCues-28: Extracting words from emotion cues for a fine-grained emotion lexicon. In Proceedings of the LREC 2016 Workshop on Emotion and Sentiment Analysis (pp. 40–47). Portorož, Slovenia. [URL]
Liew, J. S. Y., Turtle, H. R., & Liddy, E. D. (2016). EmoTweet-28: A fine-grained emotion corpus for sentiment analysis. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016) (pp. 1149–1156). Portorož, Slovenia. [URL]
2015
Liew, J. S. Y. (2015). Discovering emotions in the wild: An inductive method to identify fine-grained emotion categories in tweets. In Proceedings of the Twenty-Eighth International Florida Artificial Intelligence Research Society Conference (pp. 317-322). Hollywood, Florida, USA.
2014
McCracken, N., Liew, J. S. Y., & Crowston, K. (2014). Design of an active learning system with human correction for content analysis. In Proceedings of the ACL 2014 Workshop on Interactive Language Learning, Visualization, and Interfaces (pp. 59-62). Baltimore, Maryland, USA. [URL]
Liew, J. S. Y., McCracken, N., Zhou, S., & Crowston, K. (2014). Optimizing features in active machine learning for complex qualitative content analysis. In Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science (pp. 44–48). Baltimore, Maryland, USA. [URL]
Liew, J. S. Y. (2014). Expanding the range of automatic emotion detection in microblogging text. In Proceedings of the Student Research Workshop at the 14th Conference of the European Chapter of the Association for Computational Linguistics (pp. 38–44). Gothenburg, Sweden. DOI: 10.3115/v1/E14-3005. [URL]
Liew, J. S. Y., McCracken, N., & Crowston, K. (2014). Semi-automatic content analysis of qualitative data. In iConference 2014 Proceedings (pp. 1128–1132). Berlin, Germany. DOI: https://doi.org/10.9776/14399. [URL]
2013
Zhang, P., Liew, J. S. Y., & Hassman, K. D. (2013). The intellectual characteristics of the information field: Heritage and substance. Journal of the American Society for Information Science and Technology, 64(12), 2468–2491. DOI: https://doi.org/10.1002/asi.22941. [URL]
Liew, J. S. Y., Hassman, K., & Zhang, P. (2013). Conceptualizations of technology in the information field. In Proceedings of the American Society for Information Science and Technology, 50(1), (pp.1–3). Montreal, Quebec, Canada. DOI: https://doi.org/10.1002/meet.14505001132. [URL]
2012
Liew, J. S. Y., & Kaziunas, E. (2012). What is a tweet worth? Measuring the value of social media for an academic institution. In Proceedings of the 2012 iConference (pp. 565–566). Toronto, Ontario, Canada. DOI: https://doi.org/10.1145/2132176.2132290. [URL]
Liew, J. S. Y., Haron, F., Alginahi, Y., & Kabir, M. (2012). A preliminary crowd monitoring framework for Al- Masjid Al-Haram. In Proceedings of the 1st Taibah University International Conference on Computing and Information Technology (ICCIT 2012), Vol. 1 & 2 (pp. 111-116). Al-Madinah Al-Munawwarah, Saudi Arabia.
2011
Hussain, N., Yatim, H. S. M., Hussain, N. L., Liew, J. S. Y., & Haron, F. (2011). CDES: A pixel-based crowd density estimation system for Masjid al-Haram. Safety Science, 49(6), 824–833. DOI: https://doi.org/10.1016/j.ssci.2011.01.005. [URL]
Liew, J. S. Y., Kaziunas, E., Liu, J., & Zhuo, S. (2011). Socially-interactive dressing room: An iterative evaluation on interface design. In Proceedings of the 2011 Annual Conference Extended Abstracts on Human Factors in Computing Systems, CHI EA 2011 (pp. 2023–2028). Vancouver, British Columbia, Canada. DOI: https://doi.org/10.1145/1979742.1979925. [URL]
Supervision
PhD
Ong Yee Chiun (Main SV: Ongoing)
Wan Ahmad Luqman bin Wan Ibrisam Fikry (Main SV: Ongoing)
Liu Minkang (Main SV: Ongoing)
Aditi Gupta (Co-SV: Graduated)
Master (Research)
Aqilah Syahirah binti Shahabudin (Main SV: Ongoing)
Haitao Zhao (Main SV: Ongoing)
Lim Ying Hao (Main SV: Graduated)
Heng Yew Ken (Main SV: Graduated)
Yong Kuan Shyang (Main SV: Graduated)
Siti Aisyah Binti Mohd Fadhli (Co-SV: Graduated)
Master (Mixed-Mode)
Lim Shau Hong (Graduated-2024): Visual Instruction Tuning for Multimodal Hate Speech Detection and Explanation
Andre Tai Wei Xiang (Graduated-2024): Comparing Sentiment Lexicons to Measure Domain Similarity for Cross-domain Sentiment Analysis
Wong Kam Kang (Graduated-2023): Exploring Deep Transfer Learning for Fine-grained Emotion Classification in Product Review
Lee Su Siew (Graduated-2022): Word Sequence Emotion Classification for Storybook using Conditional Random Field
Sia Wan Yu (Graduated-2022): The Effects of Word Embeddings on Emotion Classifiers for Product Reviews
Khalaf Ayah M M (Graduated-2021): Predicting Depth-of-Knowledge based on Cognitive Processes using Machine Learning
Regina Ang Jing Wen (Graduated-2021): Analyzing Emojis in Tweets for Suicide Prediction among Celebrities using Machine Learning
Wong Hung Hing (Graduated-2021): Exploring General and Personal Models for Emoji Prediction with Ensemble Learning
Prasad A/L Madhavan (Graduated-2020): Exploring Syntactic and Semantic Features Representing Emotion Experiencer and Stimulus for Fine-grained Emotion Classification in Microblog Text
Master (Coursework-Data Science Practicum)
Lavinia Ho Pei Xian (Graduated-2022) | Mat Jasri Bin Mat Jiran (Graduated-2022) | Wong Yi Theng (Graduated-2022)
Sivanesan A/L Parasuraman (Graduated-2021) | Wong Shee Kian (Graduated-2021) | Yee Cong Jie (Graduated-2021) | Iswarya (Graduated-2021)
Elvis Yoon Yu Jing (Graduated-2020) | Chia Jia Tian (Graduated-2019) | Law Xin Yuan (Graduated-2018)
Teaching
Undergraduate Courses:
Database Organization and Design (CMT221/CMM222)
Principles of Programming (CPT111)
Master Courses:
Machine Learning (CDS503)
Recognition & Leadership
Awards & Recognition
2021 : Intel AI Global Impact Festival 2021: AI Impact Shapers Category, Country/Region Award Winner
2019 : Women of the Future Awards Southeast Asia 2019 (Science, Technology & Digital Category)
2018 : Prestige Malaysia 2018 40 under 40
2017 : L'Oréal-UNESCO for Women in Science National Fellowship Award 2017
2017 : iSchools Doctoral Dissertation Award 2017 (Runner-Up)
2016 : Syracuse University iSchool 2016 Doctoral Prize
Consultancy
Professional Trainer (HRDF-Certified TTT/23893): R for Data Science, Python and Social Media Analytics
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