Paper: Authorship Attribution with Author-aware Topic Models

ACL ID P12-2052
Title Authorship Attribution with Author-aware Topic Models
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2012

Authorship attribution deals with identifying the authors of anonymous texts. Building on our earlier finding that the Latent Dirichlet Al- location (LDA) topic model can be used to improve authorship attribution accuracy, we show that employing a previously-suggested Author-Topic (AT) model outperforms LDA when applied to scenarios with many authors. In addition, we define a model that combines LDA and AT by representing authors and doc- uments over two disjoint topic sets, and show that our model outperforms LDA, AT and sup- port vector machines on datasets with many authors.