from __future__ import print_function
import sys
import twitter
if __name__ == '__main__':
results = twitter.retrieve_tweets(topic=sys.args[1])
out = open('captured-tweets.txt', 'ab')
# The tweet is stored with key 'text',
i = 0
for result in results:
# Filter to english tweets
if result['lang'] == 'en':
out.write((result['text'] + "\n").encode('utf-8'))
i += 1
# Defaulting to capturing 5000, this takes a long time...
if i == 5000:
exit()
from __future__ import print_function
import twitter
if __name__ == '__main__':
results = twitter.retrieve_tweets(topic='weather')
# The dictionary key we are interested in 'text',
# to access it we can use our dictionary syntax d['text']
for result in results:
print(result)
# For each tweet, evaluate whether it is POSITIVE
# (by applying the model) and then if it is above
# some threshold, print it out, i.e.
# if is_positive(tweet) > 0.1 print it
from __future__ import print_function
import twitter
if __name__ == '__main__':
results = twitter.retrieve_tweets(topic='weather')
# The dictionary key we are interested in 'text',
# to access it we can use our dictionary syntax d['text']
for result in results:
print(result)
# For each tweet, evaluate whether it is POSITIVE
# (by applying the model) and then if it is above
# some threshold, print it out, i.e.
# if is_positive(tweet) > 0.1 print it
