Sentiment Analysis

What is sentiment analysis?

• Analyzing the emotion of speech

• Analyzing the sentiment of written text

• Analyzing facial expressions

• Analyzing body language

How does sentiment analysis work?

• By detecting emotional speech patterns

• By analyzing tone of voice

• By using natural language processing to determine sentiment in text

• By examining physical gestures

What are some common applications of sentiment analysis?

• Market research

• Customer feedback analysis

• Social media monitoring

• All of the above

What are the main types of sentiment that sentiment analysis detects?

• Happy, Sad, Angry

• Positive, Neutral, Negative

• Excited, Bored, Anxious

• Joyful, Fearful, Disgusted

How can sentiment analysis be used to understand customer feedback?

• By identifying keywords

• By assessing overall sentiment in customer reviews

• By tracking purchase history

• By analyzing social media usage

What are the challenges in performing sentiment analysis on social media data?

• Dealing with sarcasm and irony

• Understanding slang and abbreviations

• Handling large volumes of data

• All of the above

What are the advantages of using deep learning in sentiment analysis?

• Higher accuracy in complex texts

• Ability to process images

• Faster processing speed

• Requires less training data