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Hybrid News Sentiment Engine: real-time market analysis via ensemble learning

Researchers published a three-way ensemble sentiment model combining financial lexicons, adaptive TF-IDF clustering, and auto-calibrated weighting to ingest news headlines and price pairs without neural net training. Runs on CPU.

WHY IT MATTERS

Lightweight alternative to fine-tuned NLP models for market sentiment; trading desks can deploy without GPU infrastructure or retraining workflows, lowering ops burden and inference latency.

Source: arXiv · 2026-06-03

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Hybrid News Sentiment Engine: real-time market analysis via ensemble learning — ath