def save(self, posts, subreddit_info, get_comments):
total = 0
for post in posts:
post_sentiment = vader(post.selftext.encode('utf8'))
message = RedditMessage(_id=post.id,
text=post.selftext,
date=datetime.utcfromtimestamp(
post.created_utc),
community=subreddit_info['name'],
positive=post_sentiment['pos'],
negative=post_sentiment['neg'],
neutral=post_sentiment['neu'],
score=post.score)
comments = get_comments(post)
for comment in comments:
_sentiment = vader(comment.body.encode('utf8'))
comment_message = RedditMessage(
text=comment.body,
date=datetime.utcfromtimestamp(comment.created_utc),
community=subreddit_info['name'],
positive=_sentiment['pos'],
negative=_sentiment['neg'],
neutral=_sentiment['neu'],
score=comment.score)
# print comment
comment_message.save()
total += 1
message.save()
total += 1
logger.info('{}: saved {} messages'.format(subreddit_info['name'],
total))
def build_other_tweets(tweets):
tweets_dict = {'tweets': [], 'sentiment_count': {'Positive': 0, 'Neutral': 0, 'Negative':0}}
for tweet in tweets: #each tweet will be a Python dictionary
text = tweet['text'].encode('ascii', 'ignore')
text = ' '.join(re.sub("(@[A-Za-z0-9]+)|([^0-9A-Za-z \t])|(\w+:\/\/\S+)"," ",text).split())
text.strip()
if text == "":
continue
date = tweet['created_at'].encode('ascii', 'ignore')
retweet_count = tweet['retweet_count']
sentiment = vader(text)
if sentiment['compound'] < -0.1:
tweets_dict['sentiment_count']['Negative'] += 1
elif sentiment['compound'] > 0.1:
tweets_dict['sentiment_count']['Positive'] += 1
else:
tweets_dict['sentiment_count']['Neutral'] += 1
tweet_data = {"text" : text, "date" : date, "retweet_count" : retweet_count, "sentiment" : sentiment}
tweets_dict["tweets"].insert(0, tweet_data)
return tweets_dict
def happy_val(self): vs=vader(self.txt) if self.emoji=='': self.senti_val=vs['pos']-vs['neg'] else: txt=vs['pos']-vs['neg'] emoji=self.emoji_senti(self.emoji) self.senti_val=txt+emoji
def compute_sentiment(text):
"""
Get sentiment analysis scores for the given text.
Args:
text (str) : text on which sentiment analysis will be computed
Returns:
dictionary of sentiment scores
"""
return vader(text.encode("utf8"))
def save(self, post, community):
post_sentiment = vader(post.text.encode('utf8'))
message = TwitterMessage(
_id=post.id_str,
text=post.text,
date=post.created_at,
community=community,
positive=post_sentiment['pos'],
negative=post_sentiment['neg'],
neutral=post_sentiment['neu'],
score=post.retweet_count,
)
message.save()
return
def build_tweets_dict(tweets):
"builds tweets dictionary with raw tweeter tweets"
tweets_dict = {'tweets': []}
for tweet in tweets: #each tweet will be a Python dictionary
text = tweet['text'].encode('ascii', 'ignore')
text = ' '.join(re.sub("(@[A-Za-z0-9]+)|([^0-9A-Za-z \t])|(\w+:\/\/\S+)"," ",text).split())
text.strip()
if text == "":
continue
date = tweet['created_at'].encode('ascii', 'ignore')
retweet_count = tweet['retweet_count']
sentiment = vader(text)
tweet_data = {"text" : text, "date" : date, "retweet_count" : retweet_count, "sentiment" : sentiment}
tweets_dict["tweets"].insert(0, tweet_data)
return tweets_dict
def _compute_sentiment(self, text):
return vader(text.encode('utf8'))
if 'errors' in personalInfoResponse:
error = personalInfoResponse['errors']
print error[0]['message']
if error[0]['code'] == 50:
#user not found
search_users(name_query)
realName = personalInfoResponse['name']
handle = personalInfoResponse['screen_name']
bio = personalInfoResponse['description']
profilePicture = personalInfoResponse['profile_image_url']
coverPhoto = personalInfoResponse['profile_banner_url']
pyDictionary = {'name' : realName, 'handle' : handle, 'bio' : bio, 'profilePicture' : profilePicture, 'coverPhoto' : coverPhoto, "tweets" : []}
for item in r: #each tweet will be a Python dictionary
text = item['text'].encode('ascii', 'ignore')
date = item['created_at'].encode('ascii', 'ignore')
retweet_count = item['retweet_count']
feels = vader(text)
tempDict = {"text" : text, "date" : date, "retweet_count" : retweet_count, "feels" : feels}
pyDictionary["tweets"].append(tempDict)
jsonObjectToPassToFront = json.dumps(pyDictionary) #this object is the output
print "Success!"
