sentiment_analysis

A hybrid sentiment analysis library combining VADER (fast, rule-based) with an optional transformer backend (slower, more accurate). VADER handles most text; only ambiguous/low-confidence cases get escalated to the transformer.

Install

pip install -e .
pip install -e ".[transformer]"

Quick Start

from sentiment_analysis import SentimentAnalyzer

analyzer = SentimentAnalyzer(backend="auto", escalation_threshold=0.4)
result = analyzer.analyze("It is what it is.")
print(result)

results, stats = analyzer.analyze_batch(list_of_texts, return_stats=True)
print(stats)

Backend Modes

Known Limitations

• Confidence is derived from VADER's compound score and neutral proportion — not a calibrated probability.
• The transformer backend can be overconfident on hedged/qualified language (e.g. "only kind of good"), since it wasn't trained specifically for that nuance.