Скачать или смотреть How AI Detects Emotion From Text | Sentiment Analysis Explained

Ever noticed how the same sentence can sound happy, irritated, or sarcastic, depending on tone? Humans read emotions using voice, pauses, and facial cues. But AI may n’t have access to any of that. It only sees text.

In this episode of Truly AI, we unpack Sentiment Analysis, how machines try to detect emotions using words alone. You’ll see how AI converts words into numbers, where it works well, and why it may still need humans to truly understand context.

⏱️ Timestamps
00:00 Introduction:: Same Words, Different Feelings. A simple expression test shows why emotions are easy for humans—but hard for AI.

01:13 The three basic sentiment classes: Positive, Neutral, Negative. And why modern AI goes beyond simple labels.

02:42 Polarity, Confidence & Subjectivity. The three core scores that act as the emotional fingerprint of any sentence.

07:51 How Sentiment Models Analyze Text. Tokenization, word weights, rules, and how attention changes meaning.

10:52 Live Demo: Sentiment Workflow In Orange. Visualizing polarity, confidence and subjectivity provide sentiment for text using a real dataset.

15:58 When AI Gets It Wrong. Sarcasm, culture, and context, classic cases where sentiment models fail.

17.17 Measuring Emotion vs Feeling It. Why AI can quantify emotions but can’t truly understand them, and why humans still matter.


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