Which linguistic technique most significantly improved multilingual retail sentiment analysis accuracy in the past decade?

Sentiment analysis has revolutionized how retailers understand customer feedback across multiple languages and dialects. Linguistic technologies help companies process vast amounts of textual data from reviews, social media, and customer service interactions. This trivia question explores how computational linguistics and natural language processing have been integrated into retail analytics platforms to capture the nuances of customer sentiment across different cultural contexts.

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Transformer-based neural networks with contextual embeddings
Rule-based syntactic parsing with dictionary lookups
Simple bag-of-words frequency analysis
Statistical n-gram modeling with Bayesian inference