About Sentiment Analysis

Oracle Text enables you to perform sentiment analysis for a topic or document by using sentiment classifiers that are trained to identify sentiment metadata.

With growing amounts of data, organizations must gain more insights about their data rather than just obtaining hits in response to a search query. The insight could be in the form of answering certain basic types of queries (such as weather queries or queries about recent events) or providing opinions about user-specified topics. Keyword searches provide a list of results containing the search term. However, to identify a sentiment or opinion about the search term, must browse through the results and then manually locate the required sentiment information. Sentiment analysis provides a one-step process to identify sentiment information within a set of documents.

Sentiment analysis is the process of identifying and extracting sentiment metadata about a specified topic or entity from a set of documents. Trained sentiment classifiers identify the sentiment. When you run a query with sentiment analysis, in addition to the search results, sentiment metadata is also identified and displayed. Sentiment analysis provides answers to questions such as “Is a product review positive or negative?” or “Is the customer satisfied or dissatisfied?” For example, from a document set consisting of multiple reviews for a particular product, you can determine an overall sentiment that indicates if the product is good or bad.