My first research line focuses on developing statistical and explainable machine learning methods for analyzing complex psychological data.
TextSEM: Integrating text data into structural equation modeling.1[R package]
NeuralSEM: Incorporating neural network into Structural Equation Modeling.2
A Transformer-based framework for knowledge tracing with high predictive accuracy and interpretability.3[preprint]
A guide on using neural network to analyze psychological dataset.4[preprint]
Bass-Ackward Method on identifying the number of factors in factor analysis. 5[paper][online app]
Empathetic AI for Mental Health Support
My second research line leverages AI-driven techniques to enhance online mental health support, potentially reaching individuals who might otherwise lack access to timely assistance.
BLASH: An LLM-based writing assistant for peer-to-peer mental health support in online forums.6[video demo]
MHKG: Improving mental health support response generation with event-based knowledge graph.7[paper]
Leveraging LLMs for Suicide Intervention in Online Crisis Counseling.8
Text Mining on Social Bias and Sentiment
My third research line employs quantitative and computational methods to explore gender bias, particularly focusing on women’s experiences across digital platforms and their implications in broader social, cultural, and educational spheres.
Investigating gender bias in teaching evaluation via Large Language Models.9
Digital and historical exclusivity in feminine linguistics: from Nüshu to Xiaohongshu.10[paper]
Structured Gender Bias: How is gender cognition changed and affected by digital communities in China? 11
Quantitative analysis on the communication of COVID-19 related social media rumors.12[paper]
1.Tong, L., & Zhang, Z. (under review). TextSEM: Structural Equation Modeling for Text Data. Submitted to Structural Equation Modeling: A Multidisciplinary Journal.↩
2.Tong, L. (in prep). Incorporating Text as High Dimensional Data in Structural Equation Modeling. Dissertation.↩
3.Lu, Y., Tong, L., & Cheng, Y. (in press). Advanced Knowledge Tracing for Intelligent Tutoring Systems: Incorporating Process Data and Curricula Information via an Attention-Based Framework for Accuracy and Interpretability. Journal of Educational Data Mining.↩
4.Tong, L., & Zhang, Z. (under review). Neural Network Analysis of Psychological Data: A Step-by-Step Guide. Submitted to Multivariate Behavioral Research.↩
5.Tong, L., Qu, W., & Zhang, Z. (2024). Comparison of the K1 Rule, Parallel Analysis, and the Bass-Ackward Method on Identifying the Number of Factors in Factor Analysis. Fudan Journal of the Humanities and Social Sciences, 1-28.↩
6.Tong, L., Nguyen, B., Dang H., Hoq, A., Jiang M., & Li T. (in prep). An LLM-based Writing Assistant for Peer-to-Peer Mental Health Support in Online Forums.↩
7.Tong, L., Liu, Q., Yu, W., Yu, M., Zhang, Z., & Jiang, M. (2023). Improving mental health support response generation with event-based knowledge graph. Workshop on Knowledge-Augmented Methods for NLP (KnowledgeNLP) at AAAI Conference on Artificial Intelligence (AAAI).↩
8.Tong, L., Turpin M., Crockett N., Zhang Z., & Jiang M. (in prep). Leveraging Large Language Models for Suicide Intervention in Online Crisis Counseling.↩
9.Tong, L., Krush A., & Zhang, Z. (in prep). Investigating Gender Bias in Teaching Evaluation via Large Language Models.↩
10.Wan, R., & Tong, L. (2023). Digital and Historical Exclusivity in Feminine Linguistics: From Nüshu to Xiaohongshu. WiNLP workshop at Conference on Empirical Methods in Natural Language Processing (EMNLP).↩
11.Zhang, J., Chen, H., & Tong, L. (2022). Structured Gender Bias: How is Gender Cognition Changed and
Affected by Digital Communities in China? Annual Conference of International Association for
Media and Communication Research Conference (IAMCR).↩
12.Chen, H., Jin S., Lin W., Zhu Z., Tong L., Liu Y., ... & Sun M. (2021). Quantitative analysis on the Communication of COVID-19 Related Social Media Rumors. (In Chinese). Journal of Computer Research and Development, 58(7), 1366-1384.↩