Instruction: Define stopwords and explain their significance in NLP.
Context: This question aims to assess the candidate's understanding of common preprocessing steps in text analysis.
The way I'd explain it in an interview is this: Stopwords are very common words like "the," "and," or "is" that may carry little discriminative value in some NLP tasks. People often remove them to reduce noise and dimensionality in older or simpler pipelines.
But I would not remove them automatically. In some tasks, stopwords matter for meaning, sentiment, or syntax. Their value depends on the model and use case.
What matters in an interview is not only knowing the definition, but being able to connect it back to how it changes modeling, evaluation, or deployment decisions in practice.
A weak answer says stopwords are useless words, which is too broad and ignores tasks where they matter.