EVENT5Ws is a new large-scale, manually verified open-domain event extraction dataset that benchmarks LLMs and demonstrates cross-context generalization.
VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text
6 Pith papers cite this work. Polarity classification is still indexing.
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Convexification enables reliable solutions of Mean Field Games whose predicted sentiment densities align with observed COVID-19 social media discussion patterns.
Transformer-derived sentiment features from therapy sessions correlate with emotional-valence components of the OQ-45 and differ significantly between patients identified as at risk of deterioration by rational and empirical outcome models.
MODEE is a multimodal system that integrates graphs with LLM embeddings to outperform prior open-domain event extraction methods on large datasets.
Empirical analysis of social media discussions shows anti-conformity: individuals match the majority's judgment valence but diverge in stance, with rising persuasive language after group exposure.
Empirical study of 70 disaster apps finds heavy focus on response phase, limited preparedness/recovery support, and user issues in reliability/usability, yielding design recommendations.
citing papers explorer
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EVENT5Ws: A Large Dataset for Open-Domain Event Extraction from Documents
EVENT5Ws is a new large-scale, manually verified open-domain event extraction dataset that benchmarks LLMs and demonstrates cross-context generalization.
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Toward Practical Forecasts of Public Sentiments via Convexification for Mean Field Games: Evidence from Real World COVID-19 Discussion Data
Convexification enables reliable solutions of Mean Field Games whose predicted sentiment densities align with observed COVID-19 social media discussion patterns.
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The Association of Transformer-based Sentiment Analysis with Symptom Distress and Deterioration in Routine Psychotherapy Care
Transformer-derived sentiment features from therapy sessions correlate with emotional-valence components of the OQ-45 and differ significantly between patients identified as at risk of deterioration by rational and empirical outcome models.
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A Multimodal Text- and Graph-Based Approach for Open-Domain Event Extraction from Documents
MODEE is a multimodal system that integrates graphs with LLM embeddings to outperform prior open-domain event extraction methods on large datasets.
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Influence of the majority group on individual judgments in online spontaneous conversations
Empirical analysis of social media discussions shows anti-conformity: individuals match the majority's judgment valence but diverge in stance, with rising persuasive language after group exposure.
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Engineering for Crisis Management: A User-Centred Analysis of Disaster Mobile Applications
Empirical study of 70 disaster apps finds heavy focus on response phase, limited preparedness/recovery support, and user issues in reliability/usability, yielding design recommendations.