def __call__(self, files=None, verbose=True):
if verbose:
print(f'\nProcessing files...')
print(f'\nProcessing sentiment...')
SentimentAnalysis.__call__(self, files=files)
if verbose:
print(f'\nProcessing opinion fact...')
FactOpinion.__call__(self, files=files)
gc.collect()
if verbose:
print('\nDone !')
sep=';',
error_bad_lines=False)
countNegative = 0
countPositive = 0
countNetural = 0
df1 = data['text']
with open('visitor/Pier21winter/out2013Pier21vistorwinter.csv',
'w') as outfile:
writer = csv.writer(outfile)
writer.writerow(["text", "Sentiment", "Score"])
for row in df1.iteritems():
s = SentimentAnalysis(filename='SentiWordNet.txt',
weighting='geometric')
textt = row[1]
if s.score(textt) == 0.0:
senti = "netural"
countNetural = countNetural + 1
if s.score(textt) < 0.0:
senti = "negative"
countNegative = countNegative + 1
if s.score(textt) > 0.0:
senti = "positive"
countPositive = countPositive + 1
writer.writerow(
[textt.encode('unicode-escape'), senti,
s.score(textt)])
writer.writerow([countNetural, countNegative, countPositive])
def test_get_sentiment_socre_english(self):
text = "Happiness is unreachable thing. Because it's impossible."
analyzedResult = SentimentAnalysis(text)
analyzedResult.analyze()
print(analyzedResult.get_sadness_score())
print(analyzedResult.get_anger_score())
print(analyzedResult.get_anxiety_score())
# print(analyzedResult.get_agony_score())
print(analyzedResult.get_embarrassed_score())
print(analyzedResult.get_happiness_score())
print(analyzedResult.get_total_score())
print(analyzedResult.get_positive_score())
print(analyzedResult.get_neutral_score())
print(analyzedResult.get_negative_score())
def test_get_sentiment_score(self):
text = "너무나 우울해서 미칠 것만 같다. 나는 왜 이러는 것일까"
analyzedResult = SentimentAnalysis(text)
analyzedResult.analyze()
print(analyzedResult.get_sadness_score())
print(analyzedResult.get_anger_score())
print(analyzedResult.get_anxiety_score())
print(analyzedResult.get_agony_score())
print(analyzedResult.get_embarrassed_score())
print(analyzedResult.get_happiness_score())
print(analyzedResult.get_total_score())
print(analyzedResult.get_positive_score())
print(analyzedResult.get_negative_score())
def get_sentiment_analysis():
if not sa:
sa = SentimentAnalysis()
return sa
data = pd.read_csv('visitor/HalifaxHarboursummer/2016HalifaxHarbourvistorsummer.csv', sep=';', error_bad_lines=False)
countNegative=0
countPositive=0
countNetural=0
df1 = data['text']
with open('visitor/HalifaxHarboursummer/out2016HalifaxHarbourvistorsummer.csv', 'w') as outfile:
writer = csv.writer(outfile)
writer.writerow(["text","Sentiment","Score"])
for row in df1.iteritems():
s = SentimentAnalysis(filename='SentiWordNet.txt', weighting='geometric')
textt = row[1]
if s.score(textt)==0.0:
senti="netural"
countNetural=countNetural+1
if s.score(textt)<0.0:
senti = "negative"
countNegative=countNegative+1
if s.score(textt) > 0.0:
senti = "positive"
countPositive=countPositive+1
writer.writerow(
[textt.encode('unicode-escape'),senti, s.score(textt)])
writer.writerow([countNetural, countNegative, countPositive])
def __init__(self, main_dir):
FactOpinion.__init__(self, main_dir)
SentimentAnalysis.__init__(self, main_dir)
self.head = self.columns + list(self.entity_dict.keys()) + list(
self.tag_dict.keys()) + list(self.dep_dict.keys())