DeTox-Fed uses federated graph neural networks on local conversation graphs to detect toxic discussions in the Fediverse while keeping all raw data and labels on individual instances.
Mark my words!: linguistic style accommodation in social media , url =
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
Presents MBFC-2025 dataset and multi-view embeddings with fusion methods for media bias and factuality, reporting SOTA results on ACL-2020 and new benchmarks on MBFC-2025.
LLM responses mirror venting with higher regulation and escalation; therapist personas lower escalation while preserving regulation, and lay raters miss escalation.
New Zealand Reddit users link language to place and form contiguous speech communities with complex geographic alignment; Word2Vec embeddings reveal semantic variations and shifts in NZ English on a 4.26 billion word corpus.
citing papers explorer
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DeTox-Fed: Detecting Toxic Conversations in the Fediverse with Federated Graph Neural Networks
DeTox-Fed uses federated graph neural networks on local conversation graphs to detect toxic discussions in the Fediverse while keeping all raw data and labels on individual instances.
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A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis
Presents MBFC-2025 dataset and multi-view embeddings with fusion methods for media bias and factuality, reporting SOTA results on ACL-2020 and new benchmarks on MBFC-2025.
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When Support Escalates Distress: Regulation and Escalation in LLM Responses to Venting and Advice-Seeking
LLM responses mirror venting with higher regulation and escalation; therapist personas lower escalation while preserving regulation, and lay raters miss escalation.
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Language, Place, and Social Media: Geographic Dialect Alignment in New Zealand
New Zealand Reddit users link language to place and form contiguous speech communities with complex geographic alignment; Word2Vec embeddings reveal semantic variations and shifts in NZ English on a 4.26 billion word corpus.