TextBlob vs. VADER For Sentiment Analysis Using Python
TextBlob and VADER are two of the most widely used sentiment analysis Python libraries. Compared to machine learning approaches for sentiment analysis, TextBlob and VADER use a lexicon-based method. The lexicon approach has a mapping between words and sentiment, and the sentiment of a sentence is the aggregation of the sentiment of each term.
In this tutorial, we will compare the performance of TextBlob and VADER using sample sentences and see which one performs better. You will learn:
👉 What’s the difference between TextBlob and VADER?
👉 How to generate and interpret sentiment scores using TextBlob and VADER?
👉 When to use TextBlob vs. VADER for sentiment analysis?
⏰ Timecodes ⏰
0:00 - Intro
1:03 - Step 1: Import Libraries
1:17 - Step 2: Define Functions For VADER And TextBlob
1:25 - Step 3: Check Sentiment Difference
1:35 - Step 4: Check Impact Of Capitalization
1:55 - Step 5: Check Impact Of Repeated Words
2:21 - Step 6: Check Impact Of Punctuation
2:30 - Step 7: Check Impact Of Emojis
3:03 - Summary
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