check for profanity in a tweet
we take degree of profanity = no. of racist slurs/ length of tweet
execute profanity_checker.py
by default it looks for a tweets.json
in the same director
modify the tweets_path
var
if you want to change the list of racial slurs to include
modify the slurs
list
the json file has to be a dictionary with keys as the user name and
as values as the corresponding tweet
an example:
{
'user1': "i hate slur1 people",
'user2': "today was a good day",
'user3': "why did god create slur1s, slur2s and slur3s ugh",
'user4': "slur3s dont belong is slur4s' streets",
'user5': "the presidents new policy is bad news for the slur4s",
}