What type of feedback is needed for sentiment analysis in labels?

For sentiment analysis, customer feedback where sentiment is expressed is essential because it provides the necessary emotional context that the analysis aims to capture. Sentiment analysis relies on understanding opinions, feelings, and emotions that can be derived from the language used by customers. When feedback explicitly conveys positive, negative, or neutral sentiments, it serves as a rich data source for training machine learning models to detect similar sentiments in new, unseen data.

Neutral perspectives, while valuable, do not provide sufficient variation in sentiment and are less useful for distinguishing between emotional responses. Generic responses lack specificity and personal insights, making it difficult for sentiment analysis to draw meaningful conclusions. Technical feedback may contain objective information but does not reflect customer emotions or opinions, which are crucial elements in sentiment analysis. Therefore, feedback that includes expressed sentiment stands out as the most beneficial for building effective sentiment analysis models.