Sentiment analysis can be challenging due to the ambiguity of language. The sentiment expressed in a sentence may depend heavily on the context, sarcasm, or the overall tone of the document.
Domain Specificity:
Sentiment analysis models trained on general datasets may not perform well in domain-specific contexts. Domain-specific sentiment lexicons and fine-tuning on domain-specific data are often needed.
Handling Negation and Modifiers:
Negations and modifiers can significantly alter the sentiment of a sentence. Effective sentiment analysis models need to account for the impact of words like “not” or modifiers like “very.”
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