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Quiz Part VII: Case Studies
Chapter 17: Case Study 2 - Social Media Sentiment Analysis
- What is tokenization in the context of text preprocessing?
- A) Converting text to upper case
- B) Breaking text into individual words or sub-words
- C) Removing special characters from text
- D) Translating text into another language
- Which algorithm is commonly used for sentiment analysis?
- A) Linear Regression
- B) Naive Bayes
- C) K-Nearest Neighbors
- D) ARIMA
- Why is data collection important in social media sentiment analysis?
- A) To have sufficient data for training
- B) To better understand the audience
- C) To identify key features for model training
- D) All of the above
Chapter 17: Case Study 2 - Social Media Sentiment Analysis
- What is tokenization in the context of text preprocessing?
- A) Converting text to upper case
- B) Breaking text into individual words or sub-words
- C) Removing special characters from text
- D) Translating text into another language
- Which algorithm is commonly used for sentiment analysis?
- A) Linear Regression
- B) Naive Bayes
- C) K-Nearest Neighbors
- D) ARIMA
- Why is data collection important in social media sentiment analysis?
- A) To have sufficient data for training
- B) To better understand the audience
- C) To identify key features for model training
- D) All of the above
Chapter 17: Case Study 2 - Social Media Sentiment Analysis
- What is tokenization in the context of text preprocessing?
- A) Converting text to upper case
- B) Breaking text into individual words or sub-words
- C) Removing special characters from text
- D) Translating text into another language
- Which algorithm is commonly used for sentiment analysis?
- A) Linear Regression
- B) Naive Bayes
- C) K-Nearest Neighbors
- D) ARIMA
- Why is data collection important in social media sentiment analysis?
- A) To have sufficient data for training
- B) To better understand the audience
- C) To identify key features for model training
- D) All of the above
Chapter 17: Case Study 2 - Social Media Sentiment Analysis
- What is tokenization in the context of text preprocessing?
- A) Converting text to upper case
- B) Breaking text into individual words or sub-words
- C) Removing special characters from text
- D) Translating text into another language
- Which algorithm is commonly used for sentiment analysis?
- A) Linear Regression
- B) Naive Bayes
- C) K-Nearest Neighbors
- D) ARIMA
- Why is data collection important in social media sentiment analysis?
- A) To have sufficient data for training
- B) To better understand the audience
- C) To identify key features for model training
- D) All of the above