def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
# TODO
positive, negative, neutral = 0.0, 0.0, 0.0
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
analyzer = Analyzer(positives, negatives)
tweets = helpers.get_user_timeline(screen_name, 100)
if tweets == None:
return redirect(url_for("index"))
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, count=100)
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
# calculate the number of positive, negative and neutral tweets
positive, negative, neutral = 0.0, 0.0, 0.0
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
if tweets == None:
return redirect(url_for("index"))
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer and sentiment values
analyzer = Analyzer(positives, negatives)
positive, negative, neutral = 0.0, 0.0, 0.0
# for each tweet, determine overall sentiment and increase sentiment score accordingly
for i in range(len(tweets)):
score = analyzer.analyze(tweets[i])
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
# TODO
positive, negative, neutral = 0.0, 0.0, 0.0
analyzer = Analyzer('positive-words.txt', 'negative-words.txt')
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0:
positive += 1
elif score < 0:
negative += 1
else:
neutral += 1
positive /= len(tweets)
negative /= len(tweets)
neutral /= len(tweets)
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def visualisation():
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
tweets = helpers.get_user_timeline(screen_name, 200)
positives = "static/SentiWS_v18c_Positive.txt"
negatives = "static/SentiWS_v18c_Negative.txt"
poENG = "static/positive-words.txt"
neENG = "static/negative-words.txt"
analyzer = Analyzer(positives, negatives, poENG, neENG)
positive = 0
negative = 0
for tweet in tweets:
tweet['score'] = analyzer.analyze(tweet['tweet'])
if tweet['score'] > 0.0:
positive += tweet['score']
elif tweet['score'] < 0.0:
negative -= tweet['score']
chart = helpers.chart(positive, negative)
# render results
return render_template("visualisation.html",
chart=chart,
screen_name=screen_name,
tweets=tweets)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
# classifies tweets
positive, negative, neutral = 0, 0, 0
for tweet in tweets:
score = analyzer.analyze(tweet)
# if score is neutral
if (score == 0):
neutral += 1
elif (score > 0):
positive += 1
else:
negative += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
# TODO
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
positive, negative, neutral = 0.0, 0.0, 0.0
# analyze text
for i in range(0, 200):
score = analyzer.analyze(tweets[i])
if score > 0.0:
print(colored(str(tweets[i]), "green"))
positive = positive + 1
elif score < 0.0:
print(colored(str(tweets[i]), "red"))
negative = negative + 1
else:
print(colored(str(tweets[i]), "yellow"))
neutral = neutral + 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
# If user doesn't exist / has private account - redirect to start page.
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
if not tweets:
return redirect(url_for("index"))
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# Instantiate analyzer.
analyzer = Analyzer(positives, negatives)
positive, negative, neutral = 0.0, 0.0, 100.0
# Get percentage of sentiment for each word in a tweet.
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
positive += 100 / len(tweets)
elif score < 0.0:
negative += 100 / len(tweets)
else:
neutral += 100 / len(tweets)
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
if tweets == None:
sys.exit(colored("Unexpected error!", "red"))
positive, negative, neutral = 0.0, 0.0, 0.0
for tweet in tweets:
score = analyzer.analyze(tweet)
if score < 0.0:
negative +=1.0
elif score > 0.0:
positive += 1.0
else:
neutral += 1.0
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return render_template("error index.html")
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
if tweets == []:
return render_template("error index.html")
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
positive, negative, neutral = 0.0, 0.0, 0.0
for tweet in tweets:
temp = analyzer.analyze(tweet)
if temp > 0:
positive += 1
elif temp < 0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive / (positive + negative + neutral),
negative / (positive + negative + neutral),
neutral / (positive + negative + neutral))
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
analyzer = Analyzer(positives, negatives)
analyzer.getTweetTokens(screen_name)
positive = analyzer.classifications["positives"] / analyzer.total_tweets
negative = analyzer.classifications["negatives"] / analyzer.total_tweets
neutral = analyzer.classifications["neutrals"] / analyzer.total_tweets
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, count=100)
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
anz = Analyzer(positives, negatives)
po = ne = nu = 0
for tweet in tweets:
if anz.analyze(tweet) > 0:
po += 1
elif anz.analyze(tweet) < 0:
ne += 1
else:
nu += 1
positive, negative, neutral = po / len(tweets) * 100, ne / len(
tweets) * 100, nu / len(tweets) * 100
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
# initialise percentages
positive, negative, neutral = 0.0, 0.0, 0.0
# classify each tweet and add to percentages
for tweet in tweets:
score = analyzer.analyze(tweet)
if score == 1:
positive += 1
if score == -1:
negative += 1
if score == 0:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
if (tweets == None):
sys.exit(
"Screen name doesn't exist or a screen name's tweets are private")
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
analyzer = Analyzer(positives, negatives)
positive, negative, neutral = 0.0, 0.0, 0
for tweet in tweets:
if (analyzer.analyze(tweet) > 0):
positive += 1
elif (analyzer.analyze(tweet) < 0):
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, count=100)
# the main part
positive, negative, neutral = 0.0, 0.0, 0.0
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
positive = positive + 1
elif score < 0.0:
negative = negative + 1
else:
neutral = neutral + 1
# generate chart
chart = helpers.chart(positive / len(tweets), negative / len(tweets),
neutral / len(tweets))
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
if not tweets:
return redirect(url_for("index"))
positives = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"positive-words.txt")
negatives = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"negative-words.txt")
analyzer = Analyzer(positives, negatives)
positive, negative, neutral = 0.0, 0.0, 100.0
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, count=100)
# get analyzer object and set counter to 0
positive, negative, neutral = 0.0, 0.0, 0.0
analyzer = Analyzer(os.path.join(sys.path[0], "positive-words.txt"),
os.path.join(sys.path[0], "negative-words.txt"))
# iterate through all the tweets
for i in tweets:
# calculate score and then add to counter
if analyzer.analyze(i) > 0.0:
positive += 1.0
elif analyzer.analyze(i) < 0.0:
negative += 1.0
else:
neutral += 1.0
# map all to percentage
positive = (positive / (positive + negative + neutral)) * 100.0
negative = (negative / (positive + negative + neutral)) * 100.0
neutral = (neutral / (positive + negative + neutral)) * 100.0
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
positive_total = 0
negative_total = 0
neutral_total = 0
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
if tweets == None:
return redirect(url_for("index"))
# for each tweet
for tweet in tweets:
analyzer = Analyzer(positives, negatives)
score = analyzer.analyze(tweet)
if (score > 0.0):
positive_total += 1
elif (score < 0.0):
negative_total += 1
else:
neutral_total += 1
# generate chart
chart = helpers.chart(positive_total, negative_total, neutral_total)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweetss = helpers.get_user_timeline(screen_name)
# TODO
positive, negative, neutral = 0.0, 0.0, 0.0
positives, negatives = [], []
analyzer = Analyzer(positives, negatives)
for tweet in tweetss:
score = analyzer.analyze(tweet)
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
total = (positive + negative + neutral)
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
positive, negative, neutral = 0.0, 0.0, 100.0
for i in range(len(tweets)):
tally = analyzer.analyze(tweets[i])
if tally > 0.0:
positive = positive + 1.0
neutral = neutral - 1.0
elif tally < 0.0:
negative = negative + 1.0
neutral = neutral - 1.0
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def get_tweets(screen_name):
if not screen_name:
return jsonify({'Response': '404'})
#include the tweets file
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
# tweets and scores to conform new dictionary with scores
tweets = helpers.get_user_timeline(screen_name)
scores = []
for tweet in tweets:
scores.append(analyzer.analyze(tweet))
tweets_with_scores = {}
for tweet, score in zip(tweets, scores):
tweets_with_scores[tweet] = score
return jsonify({
'Response': '200',
'tweets_with_scores': tweets_with_scores
})
def search():
# validate screen_name
screen_name = request.args.get("screen_name")
if not screen_name:
redirect(url_for("/"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
positive, negative, neutral = 0.0, 0.0, 0.0
for tweet in tweets:
score = Analyzer().analyze(tweet)
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def main():
# ensure proper usage
if len(sys.argv) != 2:
sys.exit("Usage: ./smile @username")
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
# get latest 50 tweets of the user
tweets = get_user_timeline(sys.argv[1].strip('@'), count=50)
if tweets == None:
sys.exit("User doesn't exist or is private")
# analyze tweets
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
print(colored(tweet, "green"))
elif score < 0.0:
print(colored(tweet, "red"))
else:
print(colored(tweet, "yellow"))
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
# absolute paths to lists for analysis
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
positive, negative, neutral = 0.0, 0.0, 0.0
analyzer = Analyzer(positives, negatives)
if tweets != None:
for tweet in tweets:
score = analyzer.analyze(tweet.lower())
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
else:
sys.exit("Error")
# TODO
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# classify tweets
positive, negative, neutral = 0.0, 0.0, 100.0
positive_count, negative_count, neutral_count = 0, 0, 0
if tweets is not None and len(tweets) != 0:
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
# analyze tweets
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
positive_count += 1
elif score < 0.0:
negative_count += 1
else:
neutral_count += 1
# get percentages
positive, negative, neutral = positive_count / len(tweets), \
negative_count / len(tweets), \
neutral_count / len(tweets)
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
if tweets is not None and len(tweets) != 0:
return render_template("search.html",
chart=chart,
screen_name=screen_name,
tweets=str(len(tweets)),
tweet=tweets[0])
elif len(tweets) == 0:
return render_template("search.html",
chart=chart,
screen_name=screen_name,
tweets=0,
tweet="No tweets")
else:
return render_template("search.html",
chart=chart,
screen_name=screen_name,
tweets="N/A",
tweet="Not an account")
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name,100)
# TODO
totaltweets = len(tweets)
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
positive, negative, neutral = 0.0, 0.0, 0.0
for tweet in tweets:
if analyzer.analyze(tweet)>0:
positive = positive + 1
elif analyzer.analyze(tweet)<0:
negative = negative + 1
else:
neutral = neutral + 1
positive = positive/totaltweets*100
negative = negative/totaltweets*100
neutral = neutral/totaltweets*100
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name,50)
# TODO
if tweets==None:
return redirect(url_for("index"))
obj=Analyzer()
positive, negative, neutral =0,0,0
for tweet in tweets:
tokeni=nltk.tokenize.TweetTokenizer()
tokens=tokeni.tokenize(tweet)
score=0
for word in tokens:
score=obj.analyze(word)+score
if score>0:
positive=positive+1
elif score < 0:
negative=negative+1
else:
neutral=neutral+1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
# this works because a form will be send using get not post
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# create object by passing the above arguments
analyzer = Analyzer(positives, negatives)
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
# just intializing
positive, negative, neutral = 0.0, 0.0, 100.0
# count the number of positive, negative and neutral tweets
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's last 50 tweets
tweets = helpers.get_user_timeline(screen_name, 50)
if not tweets:
sys.exit("sorry no tweets found")
# set up for analyzing and counting
positive, negative, neutral = 0.0, 0.0, 0.0
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
analyzer = Analyzer(positives, negatives)
# analyze and count each tweet
for tweet in tweets:
curScore = analyzer.analyze(tweet)
if curScore > 0.0:
positive += 1
elif curScore < 0.0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
if tweets == None:
return redirect(url_for("index"))
# TODO
positive, negative, neutral = 0.0, 0.0, 100.0
analyzer = Analyzer(positive, negative)
for tweet in tweets:
c = analyzer.analyze(tweet)
if c > 0:
positive += 1
neutral -= 1
elif c < 0:
negative += 1
neutral -= 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
# Check if tweets array contains None
if tweets is None:
sys.exit("Error: No tweets was returned!")
# Absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# Initialize an Analyze object
analyzer = Analyzer(positives, negatives)
# Initialize sentiment analysis counts for chart values
positive, negative, neutral = 0.0, 0.0, 0.0
# Iterate through tweets
for tweet in tweets:
# Return score analysis for tweet
score = analyzer.analyze(tweet)
# Increment respective sentiment analysis counts
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
# Set sentiment analysis counts to percentages
num_tweets = positive + negative + neutral
positive = positive / num_tweets
negative = negative / num_tweets
neutral = neutral / num_tweets
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name)
# TODO
positive, negative, neutral = 0.0, 0.0, 100.0
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "")
if not screen_name:
return redirect(url_for("index"))
# get screen_name's tweets
tweets = helpers.get_user_timeline(screen_name, 100)
# handle get_user_timeline errors
if tweets == None:
return redirect(url_for("index"))
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
# counts for sentiment categories
pos_count, neg_count, neut_count = 0, 0, 0
# score and assign sentiment category to each tweet
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
pos_count += 1
elif score < 0.0:
neg_count += 1
else:
neut_count += 1
whole = pos_count + neg_count + neut_count
positive, negative, neutral = (pos_count / whole), (neg_count / whole), (neut_count / whole)
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)
def search():
# validate screen_name
screen_name = request.args.get("screen_name", "").lstrip("@")
if not screen_name:
return redirect(url_for("index"))
# absolute paths to lists
positives = os.path.join(sys.path[0], "positive-words.txt")
negatives = os.path.join(sys.path[0], "negative-words.txt")
# instantiate analyzer
analyzer = Analyzer(positives, negatives)
# get screen_name's most recent 100 tweets
tweets = helpers.get_user_timeline(screen_name, 100)
# return to index if screen_name doesn't exist
if tweets == None:
return redirect(url_for("index"))
# create positive, negative and neutral count
positive, negative, neutral = 0, 0, 0
# analyze each tweet & increase corresponding sentimen count
for tweet in tweets:
score = analyzer.analyze(tweet)
if score > 0.0:
positive += 1
elif score < 0.0:
negative += 1
else:
neutral += 1
# generate chart
chart = helpers.chart(positive, negative, neutral)
# render results
return render_template("search.html", chart=chart, screen_name=screen_name)