How to Conduct Text Analysis: Data Preprocessing

In this second Text Analysis Virtual Workshop event series, we will cover data preprocessing, which is a set of steps and techniques applied to raw text data before analysis. These steps include tokenization, lowercasing, stop word removal, stemming and lemmatization, removing special characters and further text cleaning. The goal of data preprocessing is to transform and prepare the text data for further analysis, ensuring that the data is accurate, consistent and suitable for extracting meaningful insights. Join us to learn and practice how to clean, tokenize, remove stop words and perform stemming or lemmatization on text data to prepare the data corpus for text analysis.