1. guide
  2. introduction
  1. guide
  2. introduction

Guide

Sentiment Analysis

Sentiment analysis is a computational process that aims to interpret emotional implications behind a set of words. The analysis classifies the text as negative, positive, or neutral.

Negative sentiment has words or phrases that convey negative emotions such as anger, sadness, or disappointment. For example, 'Metallica's St. Anger is the worst album I've ever heard.' would be identified as negative.

On the other hand, neutral sentiment doesn't express any specific emotions. Neutral text can be exemplified by the statement 'Metallica's Kill 'Em All is pretty okay.' A phrase like 'The White Album of The Beatles is probably the best music ever made.' would be categorized as positive text.

Lexicons containing words that are linked to different emotions are frequently used by sentiment analysis algorithms. During textual analysis, these algorithms scan for words contained within a specific lexicon, assigning an emotional value to the text based on these word selections. This value is in turn employed to sort the text into negative, neutral, or positive categories.