Sentiment Detector — WhizzStep AI Lab

How Sentiment Analysis Works

📝

Tokenize

Split the sentence into individual words. Each word will be checked against the sentiment dictionary.

📚

Lexicon Lookup

Each word has a sentiment score: positive words get +1, negative words get -1. Special intensifiers (very, really) boost scores.

🔄

Handle Negation

"Not happy" = negative! The model flips the score of words that follow "not", "never", "don't", etc.

📊

Aggregate & Score

Add up all word scores, divide by sentence length, and map to positive/negative/neutral with a confidence %.

😊

Wizzy the AI Tutor

Welcome to the Sentiment Lab! 🎉 Type any sentence — a movie review, how your day was, a book opinion — and the AI will instantly detect whether it's positive 😊, negative 😠, or neutral 😐. Watch the emotion meter react in real time!

Step 1 — Detect Sentiment Live

Try a sample sentence:

0 / 500

Your sentence will appear here with colour-coded words...

😐

Enter text to analyse

😠 Negative😐 Neutral😊 Positive

📊 Analysis Stats

Total words—

Positive words—

Negative words—

Negations found—

Final score—

😊

Wizzy the AI Tutor

Now let's go word by word! The bar chart shows each word's contribution to the final sentiment score. Positive words push the bar right 🟢, negative words push left 🔴. Which single word has the most impact? Try adding "very" or "not" before a word!

Step 2 — Word-by-Word Analysis

Type a sentence to see the detailed word analysis!

😊

Wizzy the AI Tutor

Time to test your sentiment detection skills! Read each sentence and guess whether it's positive, negative, or neutral. Then see how the AI model scores it. Do you agree with the AI? Sometimes language is tricky — sarcasm, for example!

Step 3 — Guess the Sentiment!

Your score

🔥 Streak: 0

of 0 questions

Select your answer to see the AI's analysis!

😊

Wizzy the AI Tutor

The Flip Challenge! 🔄 Can you change a positive sentence to negative (or vice versa) by swapping just 1-2 words? Try replacing "love" with "hate" or "amazing" with "terrible". Watch the sentiment meter flip! This teaches you exactly which words carry the most emotional weight.

Step 4 — Flip the Feeling!

Loading challenge...

😊 Original sentence

—

✏️ Your flipped version

Edit the sentence on the right to try to flip its sentiment!

😊

Wizzy the AI Tutor

🎊 Incredible! You've mastered Sentiment Analysis — one of the most widely used NLP techniques in the world! Companies like Amazon use it for product reviews, Netflix for content ratings, hospitals for patient feedback. You're now an NLP Scientist!

😊

Sentiment Scientist Badge!

You built a real-time sentiment analyser and mastered negation handling!

😊 WhizzStep AI Lab

This certifies that

Student Name

has mastered Sentiment Analysis & NLP

NLP Scientist

Sentiment Expert

Emotion Detector

Score: — / — · whizzstep.in

Key Concepts Mastered

Sentiment Lexicon

📚 The Dictionary

A list of words with pre-assigned sentiment scores. "Fantastic" = +2, "terrible" = -2, "the" = 0.

Negation

🔄 Word Flipping

"Not happy" ≠ "happy". Negation words like "not", "never", "don't" flip the sentiment of nearby words.

Intensifiers

💪 Boosters

"Very", "extremely", "really" amplify sentiment. "Very good" is more positive than just "good".

Aspect Sentiment

🎯 Fine-Grained

Advanced NLP detects sentiment for specific aspects: "great food but terrible service" has mixed sentiment.

Sarcasm

😏 Hard Problem

"Oh great, another Monday" sounds positive but is negative. Sarcasm is still very hard for AI to detect!

Real World Uses

🌍 Applications

Product reviews (Amazon), social media monitoring (Twitter), customer support, stock market prediction!