Who Wrote When? Author Diarization in Social Media Discussions
Abstract
We are proposing a novel framework for author diarization, i.e. attributing comments in online discussions to individual authors. We consider an innovative approach that merges pre-trained neural representations of writing style with author-conditional encoder-decoder diarization, enhanced by a Conditional Random Field with Viterbi decoding for alignment refinement. Additionally, we introduce two new large-scale German language datasets, one for authorship verification and the other for author diarization. We evaluate the performance of our diarization framework on these datasets, offering insights into the strengths and limitations of this approach.
Keywords
NLP; Deep Learning; Author Diarization; Social Media
Cite as
Boenninghoff, B., Hosseini, H., Nickel, R. M., & Kolossa, D. (2024). Who Wrote When? Author Diarization in Social Media Discussions. In Al-Onaizan, Y., Bansal, M., & Chen, Y.-N. (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2024 (pp. 15721–15734). Miami, Florida, USA: Selbstverlag — Eigenverlag.Details
Publication type
Research article in proceedings (conference)
Peer reviewed
Yes
Publication status
Published
Year
2024
Conference
Empirical Methods in Natural Language Processing (EMNLP)
Venue
Miami, Florida
Book title
Findings of the Association for Computational Linguistics: EMNLP 2024
Editor
Al-Onaizan, Yaser; Bansal, Mohit; Chen, Yun-Nung
Start page
15721
End page
15734
Publisher
Selbstverlag / Eigenverlag
Place
Miami, Florida, USA
Language
English
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