De, S., Jangra, S., Agarwal, V., Johnson, J., & Sastry, N. 2023. Biases and Ethical Considerations for Machine Learning Pipelines in the Computational Social Sciences. In Ethics in Artificial Intelligence: Bias, Fairness and Beyond (pp. 99-113). Singapore: Springer Nature Singapore
Sharifian-Attar, V., De, S., Jabbari, S., Li, J., Moss, H. 2022. Analysing Longitudinal Social Science Questionnaires: Topic modelling with BERT-based Embeddings IEEE International Conference on Big Data Special session MLBD 2022
Johnson, J., Lukose, E., De, S. 2022. Privacy Pitfalls of Online Service Terms and Conditions: a Hybrid Approach for Classification and Summarization. NLLP 2022 Workshop at EMNLP
De, S., Moss, H., Johnson, J., Li, J., Pereira, H. and Jabbari, S. 2022. Engineering a machine learning pipeline for automating metadata extraction from longitudinal survey questionnaires. IASSIST Quarterly. 46, 1 (Mar. 2022)
De, S., Johnson, J., Li, J., Moss, H. and Jabbari, S. 2022. Understanding the multiple dimensions of prediction of concepts in social and biomedical science questionnaires. DiRAC Federation Project, D-FED 3.1.7
Engineering a Machine Learning Pipeline for Automating Metadata Extraction from Longitudinal Survey Questionnaires De, Suparna; Moss, Harry; Jabbari, Sanaz; Pereira, Haeron; Johnson, Jon; Li, Jenny. European DDI Users Conference 2021, Paris, France
Metadata Uplift and Machine Learning - European Perspectives. November 2023 European DDI Users Conference, Ljubljana, Slovenia
Github Repository will be made public to coincide with publication of results