Gone are the times of Mad Men when marketers and advertisers used to bring in focus groups to ask what people think and feel about a particular product or service. Today, they just need to listen and pay attention to what people are posting and tweeting on social media.

This is the reason why modern businesses, governments institutions, news agencies, and advertising agencies are so interested in sentiment analysis.

Let’s take a look at what sentiment analysis is, how it works, its challenges, and why you should care about it:

What Exactly is Sentiment Analysis?

Sentiment analysis, or opinion mining, is a Natural Language Processing (NLP) technique used to determine the inclination of people’s opinions (Positive, Negative, or Neutral) within online unstructured text. Businesses use it to measure brand health and gain information about a consumer’s perception of a product or service.

For Example
The food at the restaurant was delicious. (Positive)
The service at the restaurant was horrible. (Negative)
The quality of utensils at the restaurant was average. (Neutral)

Approaches to Sentiment Analysis

Approaches to Sentiment Analysis

Sentiment analysis incorporates Natural Language Processing (NLP) and machine learning techniques to assign sentiment scores to entities, topics and themes in a sentence or phrase.

Let’s dig in a little bit deeper and take a look at the three most common approaches to sentiment analysis: