What type of text formats can be analyzed by Sentiment analysis tools?

Sentiment analysis tools are specifically designed to analyze unstructured text. This type of text is characterized by its lack of a predefined structure, such as emails, social media posts, reviews, or open-ended survey responses. Unstructured text often contains informal language, slang, and various writing styles, making it ripe for sentiment analysis, which assesses the feelings, opinions, or attitudes expressed within that text.

Sentiment analysis algorithms process this unstructured text by employing natural language processing (NLP) techniques to understand context, identify key phrases, and determine the overall sentiment—be it positive, negative, or neutral. This capability is essential because traditional structured data formats, such as databases and spreadsheets, do not capture the nuances of human language and emotion effectively.

Other options like typed text, images with text, and printed text are not comprehensive descriptions of the data that sentiment analysis tools can process. While typed text can indeed be unstructured, the definition itself could lead to confusion. Images containing text generally require optical character recognition (OCR) before sentiment analysis can take place, and printed text alone does not inherently denote the informal and diverse nature that unstructured text embodies. Therefore, the correct answer underscores the importance of understanding and processing unstructured text for effective sentiment analysis.