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tweet_string = "Thanks to the historic TAX CUTS that I signed into law, your paychecks are going way UP, your taxes are going way DOWN, and America is once again OPEN FOR BUSINESS!"
tweet_words = tweet_string.split()
number_of_words = len(tweet_words)
print(tweet_words)
print("Number of words in this tweet is: " + str(number_of_words))
# Iterate through the words in the tweet string
print("Words in the tweet are:")
for w in tweet_words:
len_of_w = len(w)
"""
To evaluate the good or bad score of a tweet, we count the number of good and
bad words in it.
if a word is good, increase the value of good_words by one
else if a word is bad, increase the value of bad_words by one
if good_words > bad_words then it's a good tweet otherwise it's a bad tweet
"""
"""
To evaluate the good or bad score of a tweet, we first split our tweet.
We then associate each word with positive and negative values, respectively, using a dictionary.
Finally, we caculate the average word weight of a tweet, and decide if it's a good or bad one
based on that.
"""
# Break down a string into words
"""
To evaluate the good or bad score of a tweet, we first tokenize the tweet, and then
stemmize each word in our tweet. We also associate each stem with positive and negative values,
respectively, using a dictionary.
Finally, we caculate the average word weight of a tweet, and decide if it's a good or bad one
based on that.
"""
{
"thank": 1.0,
"to": 0.0,
"the": 0.0,
"histor": 0.5,
"cut": 0.0,
"that": 0.0,
"I": 0.0,
"sign": 0.0,
"""
To evaluate the good or bad score of a tweet, we first tokenize the tweet, and then
stemmize each word in our tweet. We also associate each stem with positive and negative values,
respectively, using a dictionary.
Finally, we caculate the average word weight of a tweet, and decide if it's a good or bad one
based on that.
"""
import json
f = open('sample.json')
myJson = json.load(f)
f.close()
with open('sample.json') as f:
myJson = json.load(f)
{
"consumer_key": "YOUR CONSUMER KEY",
"consumer_secret": "YOUR CUSTOMER SECRET",
"access_token_key": "YOUR ACCESS TOKEN KEY",
"access_token_secret": "YOUR ACCESS TOKEN SECRET"
}
"""
To evaluate the good or bad score of a tweet, we count the number of good and
bad words in it.
if a word is good, increase the value of good_words by one
else if a word is bad, increase the value of bad_words by one
if good_words > bad_words then it's a good tweet otherwise it's a bad tweet
"""
import json