mlsanityData to 14 Oct 2026

SynGraph: A Dynamic Graph-LLM Synthesis Framework for Sparse Streaming User Sentiment Modeling

arXiv 2503.04619 ↗First posted 6 Mar 2025cs.CLcited by 0

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Abstract (arXiv)

User reviews on e-commerce platforms exhibit dynamic sentiment patterns driven by temporal and contextual factors. Traditional sentiment analysis methods focus on static reviews, failing to capture the evolving temporal relationship between user sentiment rating and textual content. Sentiment analysis on streaming reviews addresses this limitation by modeling and predicting the temporal evolution of user sentiments. However, it suffers from data sparsity, manifesting in temporal, spatial, and combined forms. In this paper, we introduce SynGraph, a novel framework designed to address data sparsity in sentiment analysis on streaming reviews. SynGraph alleviates data sparsity by categorizing users into mid-tail, long-tail, and extreme scenarios and incorporating LLM-augmented enhancements within a dynamic graph-based structure. Experiments on real-world datasets demonstrate its effectiveness in addressing sparsity and improving sentiment modeling in streaming reviews.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 17 of its 38 references that are in the map. First posted on arXiv 6 Mar 2025.

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References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2023LLMRec: Large Language Models with Graph Augmentation for Recommendationcited by 172
  3. 2018RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systemscited by 138
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  10. 2023Robust Prompt Optimization for Large Language Models Against Distribution Shiftscited by 19
  11. 2023Contrastive Collaborative Filtering for Cold-Start Item Recommendationcited by 15
  12. 2022Encoder-Decoder Architecture for Supervised Dynamic Graph Learning: A Surveycited by 14
5 more
  1. 2023Generating Data for Symbolic Language with Large Language Modelscited by 12
  2. 2023Decoding the Silent Majority: Inducing Belief Augmented Social Graph with Large Language Model for Response Forecastingcited by 11
  3. 2019Rethinking Attribute Representation and Injection for Sentiment Classificationcited by 8
  4. 2020Improving Document-Level Sentiment Analysis with User and Product Contextcited by 7
  5. 2024Fine-grainedly Synthesize Streaming Data Based On Large Language Models With Graph Structure Understanding For Data Sparsitycited by 1

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