REVIEW 1 cited by
Deep Learning for User Comment Moderation
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
Experimenting with a new dataset of 1.6M user comments from a Greek news portal and existing datasets of English Wikipedia comments, we show that an RNN outperforms the previous state of the art in moderation. A deep, classification-specific attention mechanism improves further the overall performance of the RNN. We also compare against a CNN and a word-list baseline, considering both fully automatic and semi-automatic moderation.
Forward citations
Cited by 1 Pith paper
-
Improving Multilingual Social Media Insights: Aspect-based Comment Analysis
A new multilingual dataset and an SFT+DPO LLM pipeline for generating comment aspect terms yields small clustering improvements, but the benchmark construction and missing artifacts limit the strength of the evidence.
Discussion (0). Continue with ORCID to comment.