Assumptions & Explaination

Author: L-Salander

README.md

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 # Assignment
 Affinity Answers
+
+Assumptions:
+
+1. The input file is a text file containing one tweet per line.
+2. The set of racial slurs is provided in a text file, with one slur per line.
+3. We consider a tweet to be profane if it contains at least one racial slur.
+4. We measure the degree of profanity as the percentage of racial slurs in the tweet.
+
+Explanation:
+
+We first read in the file of racial slurs and store them in a vector called slurs. We then read in the file of tweets and store them in a vector called tweets.
+We then loop through each tweet in the tweets vector and perform the following steps:
+1. We split the tweet into individual words using the strsplit function.
+2. We count the number of racial slurs in the tweet by checking which words in the tweet are in the slurs vector and summing up the results.
+3. We calculate the degree of profanity by dividing the number of racial slurs by the total number of words in the tweet and multiplying by 100 to get a percentage.
+4. We print out the tweet and the degree of profanity using the cat function, with appropriate formatting.