Understanding Sentiment Analysis: How Companies Know What You Think

Ever wondered how companies seem to know exactly what you think about them? While they can’t read minds, they can analyze your tweets, emails, reviews, and pretty much everything else you write online. This is where sentiment analysis comes in.

What is Sentiment Analysis?

Sentiment analysis involves analyzing large volumes of text to determine the sentiment expressed — whether it’s positive, negative, or somewhere in between. It helps companies understand their customers better, deliver stronger customer experiences, and improve their brand reputation. However, it’s not without its pitfalls.

The Basics of Sentiment Analysis

Sentiment analysis is built on Natural Language Processing (NLP), which trains software to analyze and interpret text in a way that mimics human understanding. There are a couple of main approaches to this: rule-based and machine learning-based, and sometimes a hybrid of the two.

Rule-Based Approach

In the rule-based approach, the software is trained to classify certain keywords in a text-based on groups of words called “lexicons.” Lexicons are groupings of words that describe the author’s intent. For example: