Why does a sentiment analysis system relying solely on a single, topically-narrow corpus often yield inaccurate results when applied to general social media data?

💡 Explanation

The system fails because domain-specific semantic drift causes the word meanings and sentiment associations learned from the narrow corpus to differ from those used in the broader social media context. Therefore, sentiment analysis produces inaccurate results, rather than being caused by transfer learning or parser limitations.

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