6 research outputs found
Similarity Learning for Authorship Verification in Social Media
Authorship verification tries to answer the question if two documents with
unknown authors were written by the same author or not. A range of successful
technical approaches has been proposed for this task, many of which are based
on traditional linguistic features such as n-grams. These algorithms achieve
good results for certain types of written documents like books and novels.
Forensic authorship verification for social media, however, is a much more
challenging task since messages tend to be relatively short, with a large
variety of different genres and topics. At this point, traditional methods
based on features like n-grams have had limited success. In this work, we
propose a new neural network topology for similarity learning that
significantly improves the performance on the author verification task with
such challenging data sets.Comment: 5 pages, 3 figures, 1 table, presented on ICASSP 2019 in Brighton, U