What is Sentiment Analysis?

The process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral.

Sentiment Analysis also known as Opinion Mining is a field within Natural Language Processing (NLP) that builds systems that try to identify and extract opinions within text. Usually, besides identifying the opinion, these systems extract attributes of the expression e.g.:

  1.Polarity: if the speaker express a positive or negative opinion,
  2.Subject: the thing that is being talked about,
  3.Opinion holder: the person, or entity that expresses the opinion.

Currently, sentiment analysis is a topic of great interest and development since it has many practical applications. Since publicly and privately available information over Internet is constantly growing, a large number of texts expressing opinions are available in review sites, forums, blogs, and social media.

With the help of sentiment analysis systems, this unstructured information could be automatically transformed into structured data of public opinions about products, services, brands, politics, or any topic that people can express opinions about. This data can be very useful for commercial applications like marketing analysis, public relations, product reviews, net promoter scoring, product feedback, and customer service.

What Is an Opinion?

Before going into further details, let's first give a definition of opinion. Text information can be broadly categorized into two main types: facts and opinions. Facts are objective expressions about something. Opinions are usually subjective expressions that describe people’s sentiments, appraisals, and feelings toward a subject or topic.

Sentiment analysis, just as many other NLP problems, can be modeled as a classification problem where two sub-problems must be resolved:

  1.Classifying a sentence as subjective or objective, known as subjectivity classification.
  2.Classifying a sentence as expressing a positive, negative or neutral opinion, known as polarity classification.

In an opinion, the entity the text talks about can be an object, its components, its aspects, its attributes, or its features. It could also be a product, a service, an individual, an organization, an event, or a topic. As an example, take a look at the opinion below:

"The battery life of this camera is too short." A negative opinion is expressed about a feature (battery life) of an entity (camera).

"The nightsky looks so beautiful" A positive opinion is expressed about a feature (beauty) of an entity (nightsky).