Basic tasks of sentiment analysis
It defines core problems for sentiment analysis systems, but is incremental as it reviews established concepts without introducing new methods.
The paper addresses the foundational tasks of sentiment analysis, specifically subjectivity detection to separate objective from subjective sentences and aspect extraction to identify opinion targets, but does not report any experimental results or concrete numbers.
Subjectivity detection is the task of identifying objective and subjective sentences. Objective sentences are those which do not exhibit any sentiment. So, it is desired for a sentiment analysis engine to find and separate the objective sentences for further analysis, e.g., polarity detection. In subjective sentences, opinions can often be expressed on one or multiple topics. Aspect extraction is a subtask of sentiment analysis that consists in identifying opinion targets in opinionated text, i.e., in detecting the specific aspects of a product or service the opinion holder is either praising or complaining about.