In sentiment analysis, what type of data is primarily analyzed?

In sentiment analysis, the primary focus is on understanding and interpreting the emotions or opinions expressed in text data, which is typically found in social media content and customer reviews. This type of data offers rich, unstructured text that reflects public sentiment about products, services, or brands.

Social media posts, tweets, and customer reviews contain subjective opinions and emotions that can be parsed to determine whether the sentiment expressed is positive, negative, or neutral. This data is crucial for businesses looking to gauge customer perceptions and enhance their products or services based on public feedback.

On the other hand, quantitative sales data primarily deals with numerical figures and statistics, which do not provide insights into sentiment or opinion. Internal company reports often contain factual information or strategic plans and are not focused on capturing the emotional tone of customer interactions. Furthermore, technical documentation is centered around detailed explanations and specifications of products or services, lacking the subjective opinions necessary for sentiment analysis. Thus, social media content and customer reviews are the most relevant sources for conducting sentiment analysis.