Datasets:
Tasks:
Text Classification
Modalities:
Text
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
File size: 2,008 Bytes
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from credentials import CONSUMER_KEY, CONSUMER_SECRET
import tweepy, json
from time import sleep
def fetch_tweets(rows):
tweet_ids = [row['original_id'] for row in rows]
return {tweet.id_str:tweet for tweet in fetch_ids(tweet_ids) if tweet.id_str != ''}
def fetch_ids(ids):
id_lists = [ids[x:x+100] for x in range(0, len(ids), 100)]
tweets = []
for idx, id_list in enumerate(id_lists):
print('{}.'.format(len(id_lists) - idx), flush=True, end='')
tweets.extend([tweet for tweet in api.statuses_lookup(id_list, tweet_mode='extended')])
print()
return tweets
def deanon(de_anon_file, rows, tweets):
found = 0
with open(de_anon_file, 'w') as f:
for row in rows:
if row['original_id'] in tweets:
found += 1
row['text'] = tweets[row['original_id']].full_text
f.write((json.dumps(row, ensure_ascii=False) + "\n"))
print(f'Found {found} tweets out of {len(rows)}.')
def convert(anon_file, de_anon_file):
print('Fetching texts for {}'.format(anon_file))
rows = [json.loads(row) for row in open(anon_file, 'r').readlines()]
tweets = fetch_tweets(rows)
deanon(de_anon_file, rows, tweets)
if __name__ == "__main__":
try:
CONSUMER_KEY
CONSUMER_SECRET
except:
print('Edit credentials.py to add your Twitter API credentials in the first two lines (CONSUMER_KEY and CONSUMER_SECRET)')
print('See here for more information on getting API credentials: https://developer.twitter.com/en/apps')
exit(1)
auth = tweepy.AppAuthHandler(CONSUMER_KEY , CONSUMER_SECRET)
api = tweepy.API(auth, wait_on_rate_limit=True,
wait_on_rate_limit_notify=True,
retry_count=10, retry_delay=60,
retry_errors=[400] + list(range(402,599)))
print('This can take some time, so make yourself a cup of Taiwanese oolong tea and let the magic happen!')
sleep(3)
convert('ReactionGIF.ids.json', 'ReactionGIF.json')
print('That\'s it! Hope you enjoyed the ride :)')
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