Sentiment analysis MCQs December 22, 2025November 19, 2024 by u930973931_answers 15 min Score: 0 Attempted: 0/15 Subscribe 1. What is sentiment analysis? (A) Extracting subjective information to determine opinions or emotions (B) Identifying named entities in a text (C) Converting text to numerical data (D) Classifying text into categories 2. Which of the following is the main goal of sentiment analysis? (A) Categorize text into different topics (B) Determine the overall sentiment or opinion in a text (positive, negative, neutral) (C) Extract keywords from text (D) Translate text into different languages 3. What type of data is typically analyzed in sentiment analysis? (A) Text data from social media, reviews, and articles (B) Video content (C) Audio files (D) Structured data from relational databases 4. Which of the following is a sentiment analysis classification? (A) Document, Sentence, Word (B) Positive, Negative, Neutral (C) Subject, Predicate, Object (D) Verb, Noun, Adjective 5. What is the primary method used for sentiment analysis? (A) Clustering (B) Natural Language Processing (NLP) (C) Regression analysis (D) Database indexing 6. What is a common challenge in sentiment analysis? (A) Analyzing the grammatical structure of a sentence (B) Classifying text as binary only (positive/negative) (C) Handling sarcasm and irony in text (D) Managing large datasets 7. Which of the following can be used to detect polarity (positive, negative, neutral) in sentiment analysis? (A) Bag of Words (BoW) model (B) Named Entity Recognition (NER) (C) Latent Dirichlet Allocation (LDA) (D) Part-of-Speech (POS) tagging 8. Which type of sentiment analysis classifies sentiment at a document level? (A) Document-level sentiment analysis (B) Sentence-level sentiment analysis (C) Fine-grained sentiment analysis (D) Aspect-based sentiment analysis 9. What is the term for identifying specific aspects or features and analyzing sentiment about them? (A) Sentiment polarity (B) Topic modeling (C) Aspect-based sentiment analysis (D) Opinion summarization 10. In sentiment analysis, what does “polarity” refer to? (A) The intensity of sentiment (B) The emotional tone (positive, negative, neutral) (C) The overall topic or theme (D) The grammatical structure 11. Which sentiment analysis techniques can handle ambiguous words or phrases? (A) Rule-based approaches (B) Machine learning approaches (C) Lexicon-based approaches (D) All of the above 12. What is a lexicon-based sentiment analysis approach? (A) Training a machine learning model on labeled data (B) Using predefined word sets (lexicons) with known sentiment values (C) Extracting topics from text (D) Clustering text into positive, negative, or neutral 13. Which is a popular machine learning algorithm for sentiment analysis? (A) Linear Regression (B) K-means clustering (C) Random Forest (D) Support Vector Machine (SVM) 14. In sentiment analysis, the challenge of “sarcasm” is typically associated with: (A) Detecting stop words (B) Understanding grammatical structure (C) Interpreting numerical data (D) Identifying correct polarity 15. Which tools or libraries can be used for sentiment analysis? (A) OpenCV (B) NLTK (Natural Language Toolkit) (C) TensorFlow (D) All of the above