Which natural language processing technique has revolutionized how astronomy retailers analyze telescope product reviews by identifying subtle patterns in customer sentiment?

In the competitive world of astronomy retail, companies use advanced analytics to understand customer preferences for telescopes, star maps, and observation equipment. This poll tests your knowledge about how astronomy retailers analyze product reviews to improve their offerings and enhance the stargazing experience for customers. Are you a casual observer or a data constellation expert?

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Transformer-based models that can contextualize technical astronomy terminology and distinguish between issues with optics versus mechanical components
Basic keyword counting algorithms that simply tally positive and negative words in reviews
Rule-based systems that categorize reviews based on predefined astronomy jargon dictionaries
Statistical regression models that can only detect overall positive or negative sentiment without technical context