Gianluca Demartini
Kevin Roitero
Stefano Mizzaro
- Amigó, E. et al. A unifying and general account of fairness measurement in recommender systems. Information Processing and Management 60, 1 (2023), 103--115. Google Scholar
- Baeza-Yates, R. Bias on the Web. Commun. ACM 61, 6 (June 2018), 54--61.Google Scholar
- Bolukbasi, T. et al. Man is to computer programmer as woman is to homemaker? Debiasing word embeddings. Advances in Neural Information Processing Systems 29 (2016).Google Scholar
- Fan, S. et al. Socio-economic diversity in human annotations. In Proceedings of the 4th ACM Web Science Conf. 2022. (2022); 98--109.Google Scholar
- Fong, H. et al. Fairness for auc via feature augmentation. arXiv preprint arXiv:2111.12823 (2021).Google Scholar
- Franklin, M.J. et al. CrowdDB: answering queries with crowdsourcing. In Proceedings of the 2011 ACM SIGMOD Intern. Conf. on Management of Data. (2011), 61--72.Google Scholar
- Han, L. et al. Modelling user behavior dynamics with embeddings. In Proceedings of the 29th ACM Intern. Conf. on Information & Knowledge Management. (2020), 445--454.Google Scholar
- Han, L. et al. On understanding data worker interaction behaviors. In Proceedings of the 43rd Intern. ACM SIGIR Conf. on Research and Development in Information Retrieval. (2020), 269--278.Google Scholar
- Han, L., Dong, X., and Demartini, G. Iterative human-in-the-loop discovery of unknown unknowns in image datasets. In Proceedings of the AAAI Conf. on Human Computation and Crowdsourcing 9, (2021), 72--83.Google Scholar
- Johansen, J., Pedersen, T. and Johansen, C. Studying the transfer of biases from programmers to programs. arXiv preprint arXiv:2005.08231 (2020).Google Scholar
- La Barbera, D. et al. Crowdsourcing truthfulness: The impact of judgment scale and assessor bias. In European Conf. on Information Retrieval. Springer, (2020), 207--214.Google Scholar
- Luggen, M. et al. Non-parametric class completeness estimators for collaborative knowledge graphs---The case of wikidata. In Intern. Semantic Web Conf. Springer, (2019), 453--469.Google Scholar
- Lum, K., Zhang, Y., and Bower, A. De-biasing "bias" measurement. In 2022 ACM Conf. on Fairness, Accountability, and Transparency. (2022), 379--389.Google Scholar
- Nickerson, R.S. Confirmation bias: A ubiquitous phenomenon in many guises. Rev. of General Psychology 2, 2 (1998), 175--220.Google Scholar
- Otterbacher, J., Bates, J., and Clough, P. Competent men and warm women: Gender stereotypes and backlash in image search results. In Proceedings of the 2017 CHI Conf. on Human Factors in Computing Systems. (2017), 6620--6631.Google Scholar
- Otterbacher, J. et al. Investigating user perception of gender bias in image search: the role of sexism. In Proceedings of the 41st Intern. ACM SIGIR Conf. on Research and Development in Information Retrieval. (2018), 933--936.Google Scholar
- Pastaltzidis, I. et al. Data augmentation for fairness-aware machine learning: Preventing algorithmic bias in law enforcement systems. In 2022 ACM Conference on Fairness, Accountability, and Transparency. (2022), 2302--2314.Google Scholar
- Perikleous, P. et al. How does the crowd impact the model? A tool for raising awareness of social bias in crowdsourced training data. In Proceedings of the 31st ACM Intern. Conf. on Information & Knowledge Management. (2022), 4951--4954.Google Scholar
- Reinecke, K. and Bernstein, A. Improving performance, perceived usability, and aesthetics with culturally adaptive user interfaces. ACM Transactions on Computer-Human Interaction (TOCHI) 18, 2 (2011), 1--29.Google Scholar
- Sadiq, S. et al. Information Resilience: The nexus of responsible and agile approaches to information use. The VLDB J. (2022), 1--26.Google Scholar
- Sarasua, C. et al. The evolution of power and standard Wikidata editors: Comparing editing behavior over time to predict lifespan and volume of edits. Computer Supported Cooperative Work (CSCW) 28, 5 (2019), 843--882.Google Scholar
- Schick, T., Udupa, S., and Schütze, H. Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in NLP. Transactions of the Association for Computational Linguistics 9 (2021), 1408--1424.Google Scholar
- Silberzahn, R. et al. Many analysts, one data set: Making transparent how variations in analytic choices affect results. Advances in Methods and Practices in Psychological Science 1, 3 (2018), 337--356.Google Scholar
- Sutton, A. Biased embeddings from wild data: Measuring, understanding and removing. In Intern. Symp. on Intelligent Data Analysis. Springer (2018), 328--339.Google Scholar
Index Terms
- Data Bias Management
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