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TextBlob and Sentiment Analysis — Python

TextBlob and Sentiment Analysis — Python

Let’s see a very simple example to determine sentiment Analysis in Python using TextBlob.

Step#1: Execute pip install textblob on Anaconda/command prompt.

Step#2: In the your IDE, play and learn likewise —

Observation: We can see the output is categorized between two — Polarity

and Subjectivity.

Polarity is a float value within the range [-1.0 to 1.0] where 0 indicates neutral, +1 indicates a very positive sentiment and -1 represents a very negative sentiment.

Subjectivity is a float value within the range [0.0 to 1.0] where 0.0 is very objective and 1.0 is very subjective. Subjective sentence expresses some personal feelings, views, beliefs, opinions, allegations, desires, beliefs, suspicions, and speculations where as Objective sentences are factual.