| Can the crowd identify misinformation objectively? The effects of judgment scale and assessor's background K Roitero, M Soprano, S Fan, D Spina, S Mizzaro, G Demartini Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 70 | 2020 |
| Crowdco-op: Sharing risks and rewards in crowdsourcing S Fan, U Gadiraju, A Checco, G Demartini Proceedings of the ACM on Human-Computer Interaction 4 (CSCW2), 1-24, 2020 | 33 | 2020 |
| Socio-economic diversity in human annotations S Fan, P Barlas, E Christoforou, J Otterbacher, S Sadiq, G Demartini Proceedings of the 14th ACM Web Science Conference 2022, 98-109, 2022 | 9 | 2022 |
| Does Evidence from Peers Help Crowd Workers in Assessing Truthfulness? J Xu, L Han, S Fan, S Sadiq, G Demartini The Web Conference 2022, 2022 | 5 | 2022 |
| Exploring data literacy levels in the crowd–the case of COVID-19 S Fan, L Han, G Demartini, S Sadiq Proceedings of the International AAAI Conference on Web and Social Media 16 …, 2022 | 3 | 2022 |
| An Analysis of the Australian Political Discourse in Sponsored Social Media Content L Han, R Sawant, S Fan, G Kefford, G Demartini Proceedings of the 25th Australasian Document Computing Symposium, 1-5, 2021 | 2 | 2021 |
| Improving the work environment and data quality in micro-task crowdsourcing S Fan | 1 | 2023 |
| Perception of Visual Content: Differences Between Humans and Foundation Models NA Pratama, S Fan, G Demartini arXiv preprint arXiv:2411.18968, 2024 | | 2024 |
| UQ Single Column Format Inconsistency Datasets G Demartini, T Chen, S Sadiq, S Fan, J Xu, L Han, S Yu The University of Queensland, 2023 | | 2023 |
