def gather_tweets(search_parameters,n_tweets):
twitter_details_file = get_file()
twitter_access = twitter_tools.twitter_handler(twitter_details_file)
tweets = []
print "Gathering tweets...\n"
x = 1
for tweet_info in twitter_access.stream_twitter_data(search_parameters):
tweets.append(tweet_info)
if x % 10 == 0: print str(x) + " of " + str(n_tweets)
if x == n_tweets: break
x +=1
return tweets
def main():
twitter_details_file, sentiment_file = get_files()
twitter_access = twitter_tools.twitter_handler(twitter_details_file)
scores_dict = file_to_dict(sentiment_file)
track_parameter = raw_input("Enter search terms: ")
while True:
n_tweets = raw_input("Number of tweets to scan: ")
average_size = raw_input("Size of moving average: ")
try:
n_tweets = int(n_tweets)
average_size = int(average_size)
break
except:
print "Number of tweets and size of moving average must be integers!"
search_parameters = [("track", track_parameter)]
moving_average = []
x = 1
for tweet_info in twitter_access.stream_twitter_data(search_parameters):
user_parameters = [('user_id', tweet_info['user']['id']),
('count', 20), ('include_rts', 'false')]
user_tweet_list = twitter_access.get_user_data(user_parameters)
#calculate average user sentiment for 'count' number of posts
user_sentiment = get_user_sentiment(user_tweet_list, scores_dict)
tweet_sentiment = check_sentiment(tweet_info, scores_dict)
moving_average.append(tweet_sentiment - user_sentiment)
#print details
print tweet_info.get('text',
'No tweet information').encode('utf-8').lower()
print "User Sentiment: " + str(user_sentiment) + ", Tweet Sentiment: " \
+ str(tweet_sentiment) + ", Adjusted User Sentiment: " + str(tweet_sentiment-user_sentiment)
print sum(moving_average[-average_size:]) / float(
len(moving_average[-average_size:]))
print "\n"
if x == n_tweets: break
x += 1
def main():
twitter_details_file, sentiment_file = get_files()
twitter_access = twitter_tools.twitter_handler(twitter_details_file)
scores_dict = file_to_dict(sentiment_file)
track_parameter = raw_input("Enter search terms: ")
while True:
n_tweets = raw_input("Number of tweets to scan: ")
average_size = raw_input("Size of moving average: ")
try:
n_tweets = int(n_tweets)
average_size = int(average_size)
break
except:
print "Number of tweets and size of moving average must be integers!"
search_parameters = [("track", track_parameter)]
moving_average = []
x = 1
for tweet_info in twitter_access.stream_twitter_data(search_parameters):
user_parameters = [("user_id", tweet_info["user"]["id"]), ("count", 20), ("include_rts", "false")]
user_tweet_list = twitter_access.get_user_data(user_parameters)
# calculate average user sentiment for 'count' number of posts
user_sentiment = get_user_sentiment(user_tweet_list, scores_dict)
tweet_sentiment = check_sentiment(tweet_info, scores_dict)
moving_average.append(tweet_sentiment - user_sentiment)
# print details
print tweet_info.get("text", "No tweet information").encode("utf-8").lower()
print "User Sentiment: " + str(user_sentiment) + ", Tweet Sentiment: " + str(
tweet_sentiment
) + ", Adjusted User Sentiment: " + str(tweet_sentiment - user_sentiment)
print sum(moving_average[-average_size:]) / float(len(moving_average[-average_size:]))
print "\n"
if x == n_tweets:
break
x += 1
