BUSANA 7000 - Fundamentals of Business Analytics Workshop 10: Text Mining and Analysis
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Workshop 10:
Text Mining and Analysis
Question
Companies can learn a lot about customer experiences by monitoring the social media web site Twitter. The file airlinetweets.xlsx contains a sample of 36 tweets of an airline’s customers. Each tweet details customer experience and highlights the quality of service received by the customers.
Required:
1. Normalize the terms by using stemming and generate frequency bar chart and word cloud.
2. Utilize binary document-term matrix, list the five most common terms occurring in these tweets. How often does each term appear?
3. Using Jaccard’s distance to compute dissimilarity between observations, apply hierar- chical clustering employing complete linkage method to yield three clusters on the binary document-term matrix using the following tokens as variables: agent, attend, bag, damag, and rude. How many documents are in each cluster? Give a description of each cluster.
4. How could management use the results obtained in part (3)?
2023-06-26