NLP Sentiment Analysis 2

Question 1

Which challenge does 'negation handling' address in sentiment analysis?

Accepted Answer

Reversing sentiment when words like 'not' or 'never' appear

Answer

Negation handling ensures that words like 'not' flip the sentiment of subsequent words (e.g., 'not good' becomes negative).

Question 2

What is 'aspect-based sentiment analysis' (ABSA)?

Accepted Answer

Identifying sentiment toward specific aspects or features within a text

Answer

ABSA extracts sentiment at the level of specific aspects (e.g., 'battery life' or 'camera') rather than the whole review.

Question 3

Which metric is most appropriate for evaluating sentiment analysis on a highly imbalanced dataset?

Accepted Answer

F1-score

Answer

F1-score balances precision and recall, making it more informative than accuracy when class distribution is skewed.

Question 4

What does the term 'valence' refer to in sentiment analysis?

Accepted Answer

The positive or negative direction of an emotional expression

Answer

Valence captures whether an expression is positive or negative, forming the core dimension of sentiment polarity.

Question 5

Which approach is used in 'distant supervision' for sentiment analysis?

Accepted Answer

Automatically labeling data using heuristics such as review star ratings

Answer

Distant supervision exploits noisy but abundant labels (like star ratings) to train sentiment classifiers without manual annotation.

NLP Practice Test