def test_get_matplotlib_tweets(self):
"""
Check if we get the expected results for bioconductor.
"""
term = "matplotlib"
client = TwitterClient()
results = client.get_tweets(term)
client.write_results(results)
assert len(results) == 49
def input_text():
if request.method == "POST":
print(request.form)
data = request.form['submitText']
print(data)
query = data
# creating object of TwitterClient Class
api = TwitterClient()
# calling function to get tweets
# for i in range(2):
tweets = api.get_tweets(query = query, count = 100)
langP = LangProcessor()
pos = langP.get_pos(query, tweets)
text = "corpus.txt"
langP.addtoCorpus(text, tweets)
list_of_lists = []
with open("corpus.txt", "r") as f:
for line in f:
list_of_lists.append(line.split())
model = langP.build_model(list_of_lists, query)
similars = []
similars.append(model[0][0])
similars.append(model[1][0])
similars.append(model[2][0])
definition = langP.generateDefinition(query, pos, similars)
print(definition)
pos_display = ''
if 'NN' in pos:
pos_display = 'noun'
if 'VB' in pos:
pos_display = 'verb'
# if 'RB' in pos:
# pos_display =
# import pdb;pdb.set_trace()
# return jsonify(isError=False,
# message="Success",
# statusCode=200,
# stuff=data
# ), 200
return render_template("define.html", definition=definition)
def main():
# input for term to be searched and how many tweets to search
tools = Tools()
validInput = True
while True:
print("|******************************************|")
print("|Welcome to Sentimental Analysis on Twitter|")
print("|******************************************|")
searchTerm = input("Enter Keyword/Tag to search about: ").replace(" ", "")
if searchTerm.isnumeric():
print("Please enter a valid keyword")
continue
elif len(searchTerm) <= 3:
print("Please enter a keyword with more than 3 characters")
continue
while True:
noOfTerms = input("Enter how many tweets to search: (< 500): ")
if noOfTerms.isnumeric():
if int(noOfTerms) > 500:
print("Defaulting to number of tweets to 500")
noOfTerms = int(500)
else:
print("Please enter a numeric value < 500.")
continue
twitterClient = TwitterClient()
rawTweets = twitterClient.get_tweets(searchTerm, int(noOfTerms))
# clean the tweets before adding to the dictionary
if len(rawTweets) != 0:
cleanedTweets = tools.clean_tweet(rawTweets, searchTerm)
dataAnalysis = DataAnalysis(cleanedTweets)
tweetSentiment = dataAnalysis.sentimentAnalysis(searchTerm)
tweetsDict = dict()
for tweetId in cleanedTweets:
tweetLst = list()
tweetLst.append(rawTweets[tweetId])
tweetLst.append(cleanedTweets[tweetId])
tweetLst.append(tweetSentiment[tweetId])
tweetsDict[tweetId] = tweetLst
tools.write_csv(searchTerm + '.csv', 'w', tweetsDict)
validInput = True
break
else:
print("No tweets found. Please try searching another trending keyword.\n")
validInput = False
break
if not validInput:
continue
while True:
ch = input("Choose from the below options:\n\t1. Pie Chart\n\t2. Word Cloud\n\t3. Search another "
"keyword\n\t4. Exit\nEnter your choice: ")
if ch == '1':
print("Data visualisation in Pie Chart")
print("Loading...")
dataAnalysis.generatePieChart(searchTerm)
elif ch == '2':
print("Data visualisation in Word Cloud\n")
print("Loading...")
dataAnalysis.generateWordCloud(searchTerm)
elif ch == '3':
break
elif ch == '4':
print("Thank You. Good Bye!")
exit(0)
else:
print("Incorrect choice. Please re enter your choice.\n")
continue
from components import sources
from components.method import method_page
from components.dashboards import create_dashboards
from components.tweetcard import create_deck
import json
with open("locations.json", "r") as location_file:
locations = json.load(location_file)
api = TwitterClient()
tweets = []
for location in locations:
geocode = str(location['geocode'])
city_tweets = api.get_tweets(query='blm',
count=20,
geocode=geocode,
city=location['city'])
tweets = tweets + city_tweets
# picking positive tweets from tweets
# ptweets = [tweet for tweet in tweets if tweet['sentiment'] == 'positive']
# percentage of positive tweets
# print("Positive tweets percentage: {} %".format(100 * len(ptweets) / len(tweets)))
# picking negative tweets from tweets
# ntweets = [tweet for tweet in tweets if tweet['sentiment'] == 'negative']
# percentage of negative tweets
# print("Negative tweets percentage: {} %".format(100 * len(ntweets) / len(tweets)))
# percentage of neutral tweets
# print("Neutral tweets percentage: {} % \
# ".format(100 * (len(tweets) - (len(ntweets) + len(ptweets))) / len(tweets)))
def api(query):
query_limit = int(os.getenv('QUERY_LIMIT'))
api = TwitterClient()
try:
tweets = api.get_tweets(query, query_limit)
except TweepError as e:
return jsonify({
"status_code": 429,
"message": "Too many requests. Try again later"
})
if len(tweets) == 0:
return jsonify({"status_code": 400, "message": "Not a valid query"})
positive = 0
negative = 0
neutral = 0
positive_tweets = []
negative_tweets = []
neutral_tweets = []
for tweet in tweets:
sentiment = get_sentiment(tweet['text'])
if sentiment == 1:
tweet['sentiment'] = 'positive'
positive += 1
positive_tweets.append(tweet)
elif sentiment == -1:
tweet['sentiment'] = 'negative'
negative += 1
negative_tweets.append(tweet)
else:
tweet['sentiment'] = 'neutral'
neutral += 1
neutral_tweets.append(tweet)
total_per = positive + negative + neutral
positive_per = round(((positive / total_per) * 100), 2)
negative_per = round(((negative / total_per) * 100), 2)
neutral_per = round(((neutral / total_per) * 100), 2)
mean_total = positive + negative
positive_mean = round(((positive / mean_total) * 100), 2)
negative_mean = round(((negative / mean_total) * 100), 2)
positive_tweets = sorted(positive_tweets,
key=itemgetter('retweet_count'),
reverse=True)
negative_tweets = sorted(negative_tweets,
key=itemgetter('retweet_count'),
reverse=True)
neutral_tweets = sorted(neutral_tweets,
key=itemgetter('retweet_count'),
reverse=True)
positive_word_count = get_word_count(positive_tweets, query)
negative_word_count = get_word_count(negative_tweets, query)
neutral_word_count = get_word_count(neutral_tweets, query)
sentiment = ''
if abs(positive_mean - negative_mean) < 10.0:
sentiment = 'Controversial'
elif positive_mean > negative_mean:
sentiment = 'Positive'
else:
sentiment = 'Negative'
WOE_ID = 1
trending = api.get_trending(WOE_ID)
return jsonify({
'sentiment': sentiment,
'count': {
'positive': positive,
'negative': negative,
'neutral': neutral,
'total': total_per
},
'mean': {
'positive': positive_mean,
'negative': negative_mean
},
'results': {
'positive': positive_per,
'negative': negative_per,
'neutral': neutral_per
},
'status_code': 200,
'message': 'Request Successful!',
'trending': trending[:5],
'tweets': {
'positive_tweets': positive_tweets[:5],
'negative_tweets': negative_tweets[:5],
'neutral_tweets': neutral_tweets[:5]
},
'word_count': {
'positive': positive_word_count,
'negative': negative_word_count,
'neutral': neutral_word_count
},
'query': query.title()
})
def main():
twitterClient = TwitterClient()
while True:
tweets = twitterClient.get_tweets_sentiments(twitterClient.get_tweets())
twitterClient.retweet(tweets)
time.sleep(30)
