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.
What is analyzed
Any speeches, interviews, article, debate, or any input text. Mostly focusing on news,
historical speeches/articles, government to understand general idea of text without reading the entire text
Collected sentiment in from text
Sentiment
average objectivity
average polarity
Sentences
most positive
most negative
most objective
most subjective
Visualization
sentiment over time
frequency of sentiment scores
Part of speech
most used nouns
most used verbs
most used adverbs
most used adjectives
Sentiment guide
Each sentence is analyzed using machine learning algorithm to get a sentiment score. Polarity scores determine how positive or negative sentence is. Objectivity scores determine how objective or subjective each sentence is