def duygu_analizi():
file2 = open('Duyuru.txt', 'r', encoding='utf-8')
file5 = open('Duyuru_Analiz.txt', 'w', encoding='utf-8')
for duyuru in file2.readlines():
blob1 = TextBlob(duyuru)
try:
blob_eng = blob1.translate(to="en")
file5.write(str(blob1.strip())+"\
\n(Kutupluk: " +str(blob_eng.sentiment.polarity)+ \
" Öznellik: "+str(blob_eng.sentiment.subjectivity)+')\n')
except:
continue
def preprocessing(tweet, sentiment):
global count
tweet = re.sub('(www\.[^\s]+)', '', str(tweet)) # remove url
tweet = re.sub(r'https?:\/\/.*\/\w*', '', str(tweet)) # remove hyperlink
tweet = re.sub(r'&\w*', '', str(tweet)) #remove &
tweet = re.sub('@[^\s]+', '', tweet) #remove @
tweet = re.sub(r'#\w*', '', str(tweet)) #remove hashtags
tweet = re.sub(r'\$\w*', '', str(tweet)) # Remove tickers
tweet = tweet.strip(
' ') #remove white spaces from the front and end of a string
tweet = tweet.lower() # remove upper case
negations_dic = {
"isn't": "is not",
"aren't": "are not",
"wasn't": "was not",
"weren't": "were not",
"haven't": "have not",
"hasn't": "has not",
"hadn't": "had not",
"won't": "will not",
"wouldn't": "would not",
"don't": "do not",
"doesn't": "does not",
"didn't": "did not",
"can't": "can not",
"couldn't": "could not",
"shouldn't": "should not",
"mightn't": "might not",
"mustn't": "must not"
}
t = re.compile(r'\b(' + '|'.join(negations_dic.keys()) + r')\b')
tweet = t.sub(lambda x: negations_dic[x.group()], str(tweet))
tweet = re.sub('[^a-zA-Z]', ' ', str(tweet)) # take alphabet only
tweet = TextBlob(tweet).correct()
tweet = re.sub('[\s]+', ' ', str(tweet)) #Remove additional white spaces
tweet = tweet.strip(
' ') #remove white spaces from the front and end of a string
tweet = tweet.split()
ps = PorterStemmer() #removal of suffices, like “ing”, “ly”, “s”, etc
tweet = ' '.join(tweet)
length = len(tweet.split())
if length != 0:
fp2.writelines(sentiment + '\n')
fp1.writelines(tweet + '\n')
from textblob import TextBlob
with open("SentiPhraseNet/Train_Test_Unknown_Trigrams.txt",'r',encoding='utf-8') as f1:
with open("dynmi_pos_tri.txt",'a',encoding='utf-8') as f2:
with open("dynmi_neg_tri.txt",'a',encoding='utf-8') as f3:
with open("dynmi_neu_tri.txt",'a',encoding='utf-8') as f4:
for line in f1:
blob = TextBlob(line)
tran_blob = blob.translate(to = 'en' )
pol = tran_blob.sentiment.polarity
print(blob,tran_blob.sentiment.polarity)
if(pol>0.0):
#print(str(blob))
f2.write(str(blob.strip('\n'))+"\t"+(str(tran_blob))+"\t"+str(pol)+"\n")
elif(pol<0.0):
#print(str(blob))
f3.write(str(blob.strip('\n'))+"\t"+(str(tran_blob))+"\t"+str(pol)+"\n")
else:
f4.write(str(blob.strip('\n'))+"\t"+(str(tran_blob))+"\t"+str(pol)+"\n")
def answer(input,filename):
temp=[]
contents = []
cindex = -1
if(filename):
with open(filename,'r') as f:
data_in = f.read()
else:
data_in = input
data_in="1.0 Placeholder\n"+data_in
data_in = re.sub('\n{2,}','\n',data_in)
if re.search('Summary',data_in):
temp_summ = re.search('Summary',data_in).start()
data_in = data_in[:temp_summ]
# print(data_in)
if re.search('[0-9]{1,2}\.1',data_in):
temp_summ = re.search('[0-9]{1,2}\.1',data_in).start()
data_in = data_in[temp_summ:]
# print(data_in)
data_in = re.sub(r"\b(FIG)\.\s[0-9\.]{2,}s?\b", "",data_in,flags=re.IGNORECASE)
data_in = re.sub("(^|\s)(I|(II)|(III)|(IV)|(V)|(VI)|(VII)|(VIII)|(IX)|X)($|\s)","",data_in,flags=re.IGNORECASE)
paras = data_in.split("\n")
paras = [i.strip() for i in paras if i is not ""]
for ele in paras:
# print(ele)
if re.search("^[0-9]{1,2}\.[0-9]",ele):
# print(ele)
cindex+=1
contents.append([])
else:
if cindex==0:
continue
contents[cindex].append(ele)
if(input):
contents = []
contents.append([input])
# print(contents)
for text in contents:
if(input):
d=nlp(str(input))
temp_text = str(input)
# print(d)
land=[(x.text,x.label_) for x in d.ents]
final=[]
for iii in land:
if iii[1]=="PERSON" or iii[1]=="LAW":
final.append(iii[0])
for i in final:
# print(temp_text)
toappend_text=temp_text.replace(i,"____________"),
# print(temp_text[0])
temp.append((toappend_text[0],i))
global output
output=set()
if len(text)==0:
continue
text=' '.join(text)
text=re.sub(r'\’',r'',text)
text=text.lower()
text = TextBlob(text)
par_text=TextBlob("")
for sentence in text.sentences:
par_text+=paraphrase(sentence)
par_text+=" "
par_text=par_text.strip()
par_text=str(par_text)
r=Rake()
r.extract_keywords_from_text(par_text)
par_text=TextBlob(par_text)
#print(r.get_ranked_phrases())
counter=0
for i in r.get_ranked_phrases():
counter+=1
if counter>20:
break
for sentence in par_text.sentences:
if i in sentence:
pos(sentence,i)
count=0
for i in output:
count+=1
temp.append(i)
# print(i)
return temp
def Getsearch(self):
auth = OAuthHandler(self.API_KEY, self.API_SECRET_KEY)
auth.set_access_token(self.ACESS_TOKEN_KEY,
self.ACESS_TOKEN_SECRET_KEY)
api = tweepy.API(auth)
searchTerm = str(self.search1.get())
NoOfTerms = int(self.search2.get())
tweets = tweepy.Cursor(api.search, q=searchTerm,
lang="en").items(NoOfTerms)
fp1 = open("tweets.csv", 'w')
count = 1
xx = []
count = 1
for tweet in tweets:
xx.append(tweet.text)
for tweet in xx:
tweet = re.sub('(www\.[^\s]+)', '', str(tweet)) # remove url
tweet = re.sub(r'https?:\/\/.*\/\w*', '',
str(tweet)) # remove hyperlink
tweet = re.sub(r'&\w*', '', str(tweet)) #remove &
tweet = re.sub('@[^\s]+', '', str(tweet)) #remove @
tweet = re.sub(
r'#\w*', '', str(tweet)
) #remove hashtags tweet = re.sub(r'\$\w*', '', str(tweet)) # Remove tickers
tweet = tweet.strip(
' ') #remove white spaces from the front and end of a string
tweet = tweet.lower() # remove upper case
negations_dic = {
"isn't": "is not",
"aren't": "are not",
"wasn't": "was not",
"weren't": "were not",
"haven't": "have not",
"hasn't": "has not",
"hadn't": "had not",
"won't": "will not",
"wouldn't": "would not",
"don't": "do not",
"doesn't": "does not",
"didn't": "did not",
"can't": "can not",
"couldn't": "could not",
"shouldn't": "should not",
"mightn't": "might not",
"mustn't": "must not"
}
t = re.compile(r'\b(' + '|'.join(negations_dic.keys()) + r')\b')
tweet = t.sub(lambda x: negations_dic[x.group()], str(tweet))
tweet = re.sub('[^a-zA-Z]', ' ', str(tweet)) # take alphabet only
tweet = TextBlob(tweet).correct()
tweet = re.sub(r'\b\w{1,2}\b', '',
str(tweet)) # Remove words with 2 or fewer letters
tweet = re.sub('[\s]+', ' ',
str(tweet)) #Remove additional white spaces
tweet = tweet.strip(
' ') #remove white spaces from the front and end of a string
tweet = tweet.split()
ps = PorterStemmer(
) #removal of suffices, like “ing”, “ly”, “s”, etc
tweet = str(' '.join(tweet))
tweetx = "\n" + tweet + "\n"
self.TxtBox.insert(0.0, tweetx)
count = count + 1
fp1.writelines(tweet + '\n')
fp1.close()
