The DOI matches its Crossref record; 91 of the 91 references it cites were found in a registry or an index.
It’s All in the Name: A Character-Based Approach to Infer Religion
Abstract
Large-scale microdata on group identity are critical for studies on identity politics and violence but remain largely unavailable for developing countries. We use personal names to infer religion in South Asia—where religion is a salient social division, and yet, disaggregated data on it are scarce. Existing work predicts religion using a dictionary-based method and, therefore, cannot classify unseen names. We provide character-based machine-learning models that can classify unseen names too with high accuracy. Our models are also much faster and, hence, scalable to large datasets. We explain the classification decisions of one of our models using the layer-wise relevance propagation technique. The character patterns learned by the classifier are rooted in the linguistic origins of names. We apply these to infer the religion of electoral candidates using historical data on Indian elections and observe a trend of declining Muslim representation. Our approach can be used to detect identity groups across the world for whom the underlying names might have different linguistic roots.
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“This broader understanding casts a wide net for the applicability of Article 9 GDPR, as machine learning techniques increasingly allow for the deduction of protected categories from otherwise innocuous data points [35,36].”
From Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity (2024) · cites this paper as [36]
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Cited by
Generative AI in EU law: Liability, privacy, intellectual property, and cybersecurity
Novelli, C., Casolari, F., Hacker, P., Spedicato, G., & Floridi, L. (2024) · Computer Law & Security Review · doi:10.1016/j.clsr.2024.106066 · Cited by 124
Generative Ai in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity
Novelli, C., Casolari, F., Hacker, P., Spedicato, G., & Floridi, L. (2024) · doi:10.2139/ssrn.4821952 · Cited by 57
Metadata
- Authors
- Chaturvedi, R., & Chaturvedi, S.
- Venue
- Political Analysis
- Publisher
- Cambridge University Press (CUP)
- Published
- 2023-03-23
- Volume
- 32
- Issue
- 1
- Pages
- 34-49
- ISSN
- 1047-1987
- 1476-4989
- Cited by
- 18
- References
- 91
- Language
- en
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