About Performing Sentiment Analysis
To perform sentiment analysis, you run a sentiment query that includes the sentiment classifier which must be used to identify sentiment information. The classifier can be the default or a user-defined sentiment classifier.
You can perform sentiment analysis only as part of a search operation. Oracle Text searches for the specified keywords and generates a result set. Then, sentiment analysis is performed on the result set to identify a sentiment score for each result. If you do not explicitly specify a sentiment classifier in your query, the default classifier is used.
You can either identify one single sentiment for the entire document or separate sentiments for each topic within a document. Most often, a document contains multiple topics and the author’s sentiment toward each topic may be different. In such cases, document-level sentiment scores may not be useful because they cannot identify sentiment scores associated with different topics in the document. Identifying topic-level sentiment scores provides the required answers. For example, when searching through a set of documents containing reviews for a camera, a document-level sentiment tells you whether the camera is good or not. Assume that you want the general opinion about the picture quality of a camera. Performing a topic-level sentiment analysis, with “picture quality” as one of the topics provides the required information.
Note: If you do not specify a topic of interest for sentiment analysis, then Oracle Text returns the overall sentiment for the entire document.