def emotion_data(comment):
comment = comment.translate({ord(c): '' for c in string.punctuation})
sn = Senticnet()
polarity_intense = 0
comment_sentics = {
'sensitivity': 0,
'attention': 0,
'pleasantness': 0,
'aptitude': 0
}
comment_mood_tags = []
words = comment.split(" ")
total_word_count = len(words)
final_output = {
'sentics': {
'sensitivity': '0',
'attention': '0',
'pleasantness': '0',
'aptitude': '0',
'polarity': '0'
},
'mood tags': {}
}
for i in words:
try:
#word_emotion(i, sn)
polarity_intense += float(sn.polarity_intense(i))
#print sn.sentics(i)
sentics_values(i, sn, comment_sentics)
add_mood_tags(comment_mood_tags, sn, i)
except KeyError:
#print "This word does not exist", i
if (total_word_count > 1):
total_word_count -= 1
pass
comment_sentics_average(total_word_count, comment_sentics)
final_output['sentics']['polarity'] = polarity_intense / total_word_count
final_output['mood tags'] = comment_mood_tags
for output in final_output['sentics']:
if output in comment_sentics:
final_output['sentics'][output] = comment_sentics[output]
json_output = json.dumps(final_output)
print(json_output)
return json_output
def getInfo(self, concept):
try:
sn = Senticnet()
concept_info = sn.concept(concept)
polarity_value = sn.polarity_value(concept)
polarity_intense = sn.polarity_intense(concept)
moodtags = sn.moodtags(concept)
semantics = sn.semantics(concept)
sentics = sn.sentics(concept)
"""print(concept)
print("concept_info: {}".format(concept_info))
print("polarity_value: {}".format(polarity_value))
print("polarity_intense: {}".format(polarity_intense))
print("moodtags: {}".format(moodtags))
print("semantics: {}".format(semantics))
print("sentics: {}".format(sentics))
print("\n\n")"""
return "{} - {}".format(polarity_value, polarity_intense)
except:
return "NOT POSSIBLE"
from senticnet.senticnet import Senticnet
sn = Senticnet()
print "polarity value:", sn.polarity_value("love")
print "polarity intense:", sn.polarity_intense("love")
print "moodtags:", ", ".join(sn.moodtags("love"))
print "semantics:", ", ".join(sn.semantics("love"))
print "\n".join(
[key + ": " + str(value) for key, value in sn.sentics("love").items()])
for concept in concepts:
concept = concept.replace('[', '')
concept = concept.replace('u\'', '')
concept = concept.replace('_', ' ')
concept = concept.replace('...', '')
concept = concept.replace(']', '')
concept = concept.replace('\'', '')
concept = concept.split(',')
print('internal loop')
for item in concept:
print('item:')
print(item)
item = str(item)
#item='love'
try:
concept_info = sn.concept(item)
polarity_value = sn.polarity_value(item)
polarity_intense = sn.polarity_intense(item)
print(polarity_value)
moodtags = sn.moodtags(item)
semantics = sn.semantics(item)
sentics = sn.sentics(item)
polarity_intense_result.append(polarity_intense)
polarity_value_result.append(polarity_value)
concept_info_result.append(concept_info)
except:
print('Concept not in senticnet')
print(polarity_value_result)
def score_calculation(sentence):
sno = SnowballStemmer('english')
lemma = WordNetLemmatizer()
sn = Senticnet()
polarity_intense = 0
comment_sentics = {
'sensitivity': 0,
'attention': 0,
'pleasantness': 0,
'aptitude': 0
}
comment_mood_tags = []
total_word_count = len(sentence)
final_output = {
'sentics': {
'sensitivity': '0',
'attention': '0',
'pleasantness': '0',
'aptitude': '0',
'polarity': '0'
},
'mood tags': {}
}
for i in sentence:
try:
#word_emotion(i,sn)
polarity_intense += float(sn.polarity_intense(i))
sentics_values(i, sn, comment_sentics)
add_mood_tags(comment_mood_tags, sn, i)
except KeyError:
#print "This word does not exist"
try:
current_word = lemma.lemmatize(i)
#word_emotion(current_word,sn)
polarity_intense += float(sn.polarity_intense(current_word))
sentics_values(current_word, sn, comment_sentics)
add_mood_tags(comment_mood_tags, sn, current_word)
except KeyError:
#print("This didnt work again")
try:
# word_emotion(sno.stem(current_word),sn)
current_word = sno.stem(current_word)
polarity_intense += float(
sn.polarity_intense(current_word))
sentics_values(current_word, sn, comment_sentics)
add_mood_tags(comment_mood_tags, sn, current_word)
except KeyError:
if (total_word_count > 1):
total_word_count -= 1
pass
comment_sentics_average(total_word_count, comment_sentics)
final_output['sentics']['polarity'] = polarity_intense / total_word_count
final_output['mood tags'] = comment_mood_tags
for output in final_output['sentics']:
if output in comment_sentics:
final_output['sentics'][output] = comment_sentics[output]
json_output = json.dumps(final_output)
final_excitement = {'score': '0', 'mood tags': {}}
final_excitement_score = comment_sentics['attention'] + comment_sentics[
'pleasantness']
final_excitement['score'] = str(final_excitement_score)
final_excitement['mood tags'] = comment_mood_tags
#print json_output
#print final_excitement
return final_excitement