VADER — Social Media Sentiment Analyzer

VADER — Social Media Sentiment Analyzer

VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool specifically attuned to sentiments expressed in social media and marketing contexts. Unlike heavy transformer models, VADER requires no training data, runs in milliseconds, and handles emojis, capitalization, punctuation emphasis, slang, and negations out of the box — making it the go-to tool for real-time brand monitoring, ad response analysis, and customer feedback scoring.

Key Features

• Returns compound score (-1 = very negative, +1 = very positive) plus pos/neu/neg proportions
• Handles social media conventions: "GREAT!!!", "not bad", ":)", "LOL", "smh"
• 7,500+ human-validated sentiment lexicon entries
• No training required — zero-shot on any text
• Integrates directly with pandas for batch processing of review or comment datasets

Quick Start

pip install vaderSentiment

from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer

analyzer = SentimentIntensityAnalyzer()

copy_samples = [
    "Our new product launch was an AMAZING success!!!",
    "Customer complaints are through the roof this quarter.",
    "Not bad for a first campaign :)"
]
for text in copy_samples:
    scores = analyzer.polarity_scores(text)
    print(f"{scores['compound']:.2f}  {text[:50]}")

npx ai-supply add vader-sentiment-analysis

Curated mirror of the open-source vaderSentiment (MIT). Get it from the source.