The Marketing department of your company wishes to track opinion on a new product that was recently
introduced. Marketing would like to know how many positive and negative reviews are appearing over a given
period and potentially retrieve each review for more in-depth insight. They have identified several popular
product review blogs that historically have published thousands of user reviews of your company’s products.
You have been asked to provide the desired analysis. You examine the RSS feeds for each blog and
determine which fields are relevant. You then crafta regular expression to match your new product’s name and
extract the relevant text from each matching review.
What is the next step you should take?

A.
Convert the extracted text into a suitable document representation and index into a review corpus

B.
Use the extracted text and your regular expression to perform a sentiment analysis based on mentionsof
the new product

C.
Read the extracted text for each review and manually tabulate the results

D.
Group the reviews using Na.ve Bayesian classification