def emojiSentimentAnalysis(self):
final_labels = []
score_lst = []
negCount = 0
posCount = 0
neuCount = 0
for i in self.emojiList:
pos_total = 0
neg_total = 0
if len(i) > 1:
for j in i:
try:
response = get_emoji_sentiment_rank(j)
except KeyError:
continue
score = response['sentiment_score']
if score > 0:
pos_total += score
elif score < 0:
neg_total += score
else:
try:
response = get_emoji_sentiment_rank(i)
except KeyError:
continue
score = response['sentiment_score']
if score > 0:
pos_total += score
elif score < 0:
neg_total += score
# print(i)
# print(pos_total)
# print(neg_total)
if pos_total > abs(neg_total):
# print('Pos')
final_labels.append("POS")
score_lst.append(pos_total)
posCount += 1
elif pos_total < abs(neg_total):
# print('Neg')
score_lst.append(neg_total)
negCount += 1
final_labels.append("NEG")
else:
neuCount += 1
score_lst.append(0)
# print('Neu')
final_labels.append('NEU')
# print('-----------')
return {
"negativeCount": negCount,
"postiveCount": posCount,
"neutralCount": neuCount,
"score": score_lst
}
def sentiment_emoji(emoji):
try:
sentiment = get_emoji_sentiment_rank(emoji)['sentiment_score']
if sentiment < -0.3:
return '{emoji_neg}'
elif sentiment < 0.3:
return '{emoji_neu}'
elif sentiment >= 0.3:
return '{emoji_pos}'
except:
return '{emoji_na}'
def load_scores_emoji():
file = csv.reader(open("Emoji_Sentiment_Data_v1.0.csv", "r"),
delimiter=',')
for x in range(4): # strip header info
next(file)
emojis = {
row[0]: float("{:.2f}".format(
rescale(
get_emoji_sentiment_rank(row[0])["sentiment_score"], -1, 1, 1,
9)))
for row in file
}
return emojis
def compute_emoticon_score(emoticonList: list):
"""
Computes an emoticon score using emosent library
Inputs : List of emoticons
Outputs : Mean emoticon score for multiple emoji's, Score of 0 for tweets without emojis
"""
emoticon_score = []
for emoticon in emoticonList:
try:
emoticon_score.append(
get_emoji_sentiment_rank(emoticon)["sentiment_score"])
except KeyError:
emoticon_score.append(0)
if len(emoticon_score) > 0:
return sum(emoticon_score) / len(emoticon_score)
else:
return 0
def replace(text,
placeholder_pos=' POS_EMOJI ',
placeholder_neg=' NEG_EMOJI ',
placeholder_net=' NETRAL_EMOI '):
for str_ in text:
if str_ in emoji.UNICODE_EMOJI:
try:
score = get_emoji_sentiment_rank(
str_)['sentiment_score']
except KeyError:
# text = text.replace(str_, placeholder_net)
text = text.replace(str_, '')
continue
if score > 0:
text = text.replace(str_, placeholder_pos)
else:
text = text.replace(str_, placeholder_neg)
return text
def load_scores():
file1 = csv.reader(open("Hedonometer.csv", "r"), delimiter=',')
for x in range(4): # strip header info
next(file1)
file = csv.reader(open("Emoji_Sentiment_Data_v1.0.csv", "r"),
delimiter=',')
for x in range(4): # strip header info
next(file)
words = {row[1]: float(row[3]) for row in file1}
emojis = {
row[0]: float("{:.2f}".format(
rescale(
get_emoji_sentiment_rank(row[0])["sentiment_score"], -1, 1, 1,
9)))
for row in file
}
return {**words, **emojis}
def get_emoji_sentiment(emoji):
try:
return get_emoji_sentiment_rank(emoji)['sentiment_score']
except KeyError: # handle unknown emoji
return 0.5