Abstract: Natural language processing is used in sentiment analysis. It's also known as sentiment analysis or opinion mining.
It aids decision-making in humans. Various tasks, such as subjectivity identification, sentiment classification, aspect term
extraction, feature extraction, and so on, are required to perform sentiment analysis. Users can easily express their thoughts
and feelings by using social media sites such as Twitter, Facebook, and others. Millions of people share their views through
their everyday interactions on social media sites such as Twitter, Facebook, and others, which can be their sentiments and
opinions about a specific subject. These ever-increasing subjective data are unquestionably a wealth of knowledge for any
type of decision-making process. Sentiment Analysis is a field that has arisen to automate the analysis of such results. Its aim
is to recognize data on the Internet and classify it according to its polarity, or whether it has a positive or negative
connotation. Sentiment Analysis is a text-based analysis issue, but it has some problems that make it more challenging than
conventional text-based analysis.
Keywords: sentiment analysis, sentiment classification, features selection, opinion