Designing an NLP Pipeline for Sentiment Analysis
Understand how to design an efficient NLP pipeline for sentiment analysis in customer support scenarios.
In a bustling tech support center, Alex is part of a team tasked with improving customer satisfaction through better sentiment analysis of incoming emails and chat transcripts. The company recently acquired advanced natural language processing (NLP) tools but the existing pipeline lacks efficiency and accuracy, often misclassifying neutral sentiments as negative or positive. Alex's manager assigns them to design an improved NLP pipeline for more precise sentiment classification, focusing on preprocessing steps like tokenization, lemmatization, stopword removal, feature extraction with techniques such as TF-IDF, and applying machine learning models. As part of the process, Alex must decide whether to use…
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