From online reviews to social media posts, unstructured text data holds valuable insights—if you know how to extract them. In this session, you’ll learn how to turn raw text into meaningful metrics using Python, applying natural language processing (NLP) techniques to real-world data. You’ll walk through every step, from scraping the data to visualizing the results.In this code-along webinar, Maham Khan will guide you through analyzing professor ratings using the nltk package. You’ll learn how to collect and clean text data, extract quantitative features, and create visualizations that reveal patterns and sentiment. By the end, you’ll have a practical workflow you can apply to any text dataset.
Key takeaways
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Learn how to apply a web scraper to create a corpus of freelancer reviews
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Learn how to label the reviews based upon pre-defined conditions
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Identify language (words and phrases) used more often for freelancers based on different personas, and study how this language varies by field
