Abstract
Score- and feature-based methods are the two main ones for estimating a forensic likelihood ratio (LR) quantifying the strength of evidence. In this forensic text comparison (FTC) study, a score-based method using the Cosine distance is compared with a feature-based method built on a Poisson model with texts collected from 2,157 authors. Distance measures (e.g. Burrows’s Delta, Cosine distance) are a standard tool in authorship attribution studies. Thus, the implementation of a score-based method using a distance measure is naturally the first step for estimating LRs for textual evidence. However, textual data often violates the statistical assumptions underlying distance-based models. Furthermore, such models only assess the similarity, not the typicality, of the objects (i.e. documents) under comparison. A Poisson model is theoretically more appropriate than distance-based measures for authorship attribution, but it has never been tested with linguistic text evidence within the LR framework. The log-LR cost (Cllr) was used to assess the performance of the two methods. This study demonstrates that: (1) the feature-based method outperforms the score-based method by a Cllr value of ca. 0.09 under the best-performing settings and; (2) the performance of the feature-based method can be further improved by feature selection.- Anthology ID:
- 2020.alta-1.4
- Volume:
- Proceedings of the 18th Annual Workshop of the Australasian Language Technology Association
- Month:
- December
- Year:
- 2020
- Address:
- Virtual Workshop
- Editors:
- Maria Kim, Daniel Beck, Meladel Mistica
- Venue:
- ALTA
- SIG:
- Publisher:
- Australasian Language Technology Association
- Note:
- Pages:
- 32–42
- Language:
- URL:
- https://aclanthology.org/2020.alta-1.4
- DOI:
- Cite (ACL):
- Michael Carne and Shunichi Ishihara. 2020. Feature-Based Forensic Text Comparison Using a Poisson Model for Likelihood Ratio Estimation. In Proceedings of the 18th Annual Workshop of the Australasian Language Technology Association, pages 32–42, Virtual Workshop. Australasian Language Technology Association.
- Cite (Informal):
- Feature-Based Forensic Text Comparison Using a Poisson Model for Likelihood Ratio Estimation (Carne & Ishihara, ALTA 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2020.alta-1.4.pdf