def get_sentiment_polarity_score(text):
analyzer = oseti.Analyzer()
score = analyzer.analyze(text)
if (len(score) > 0):
return sum(score) / len(score)
else:
return 0
def pn_oseti(text):
analyzer = oseti.Analyzer()
tmp = analyzer.analyze(text)
pn_sum = sum(tmp)
pn_average = sum(tmp) / len(tmp)
return pn_sum, pn_average
def test_analyze(self):
a = oseti.Analyzer()
text = '遅刻したけど楽しかったし嬉しかった。すごく充実した！'
actual = a.analyze(text)
assert_equal(actual, [0.3333333333333333, 1.0])
text = 'そこにはいつもと変わらない日常があった。'
actual = a.analyze(text)
assert_equal(actual, [0.0])
def test_lookup_wago(self):
a = oseti.Analyzer()
actual = a._lookup_wago('うんざり', [])
assert_equal(actual, 'うんざり')
actual = a._lookup_wago('軽い', ['尻', 'が'])
assert_equal(actual, '尻 が 軽い')
actual = a._lookup_wago('どうでもいい', [])
assert_equal(actual, '')
def test_calc_sentiment_polarity(self):
a = oseti.Analyzer()
actual = a._calc_sentiment_polarity('最高な仕事')
assert_equal(actual, 1)
actual = a._calc_sentiment_polarity('貪欲じゃないじゃない。')
assert_equal(actual, -1)
actual = a._calc_sentiment_polarity('どうでもいい')
assert_equal(actual, 0)
def test_count_polarity(self):
a = oseti.Analyzer()
text = '遅刻したけど楽しかったし嬉しかった。すごく充実した！'
actual = a.count_polarity(text)
assert_equal(actual, [{'positive': 2, 'negative': 1}, {'positive': 1, 'negative': 0}])
text = 'そこにはいつもと変わらない日常があった。'
actual = a.count_polarity(text)
assert_equal(actual, [{'positive': 0, 'negative': 0}])
def calculate_score():
sentence = request.args.get('q')
print('Sentence', sentence)
analyzer = oseti.Analyzer()
score_list = analyzer.analyze(sentence)
score = sum(score_list) / len(score_list)
print('Score:', score)
return (jsonify(score=score))
def test_analyze_detail(self):
a = oseti.Analyzer()
text = '遅刻したけど楽しかったし嬉しかった。すごく充実した！'
actual = a.analyze_detail(text)
assert_equal(actual, [{'positive': ['楽しい', '嬉しい'], 'negative': ['遅刻'], 'score': 0.3333333333333333},
{'positive': ['充実'], 'negative': [], 'score': 1.0}])
actual = a.analyze_detail('お金も希望もない！')
assert_equal(actual, [{'positive': [], 'negative': ['お金-NEGATION', '希望-NEGATION'], 'score': -1.0}])
actual = a.analyze_detail('お金がないわけではない')
assert_equal(actual, [{'positive': ['お金'], 'negative': [], 'score': 1.0}])
def posi_nega_jud(self):
analyzer = oseti.Analyzer() # type: Analyzer
posinega_text_list = analyzer.count_polarity(self.text) # type: list
for i in range(len(posinega_text_list)):
if posinega_text_list[i]['positive'] > 0:
self.posinega_score += posinega_text_list[i]['positive']
if posinega_text_list[i]['negative'] > 0:
self.posinega_score -= posinega_text_list[i]['negative']
self.tangoNum = len(posinega_text_list)
return self.posinega_score, self.tangoNum
def score(texts):
# see: https://github.com/ikegami-yukino/oseti
analyzer = oseti.Analyzer()
count = 0
total_score = 0
for text in texts:
try:
txt_scores = analyzer.analyze(text.get('text'))
if len(txt_scores) == 0:
continue
total_score += np.average(txt_scores)
except IndexError:
print("error起きたけどながしとくわ！")
return total_score
def test_calc_sentiment_polarity(self):
a = oseti.Analyzer()
actual = a._calc_sentiment_polarity('最高な仕事')
assert_equal(actual, [['最高', 1]])
actual = a._calc_sentiment_polarity('貪欲じゃないじゃない。')
assert_equal(actual, [['貪欲', -1]])
actual = a._calc_sentiment_polarity('どうでもいい')
assert_equal(actual, [])
actual = a._calc_sentiment_polarity('お金も希望もある')
assert_equal(actual, [['お金', 1], ['希望', 1]])
actual = a._calc_sentiment_polarity('お金とか希望なりない')
assert_equal(actual, [['お金-NEGATION', -1], ['希望-NEGATION', -1]])
actual = a._calc_sentiment_polarity('お金だの希望だの喜びだのない')
assert_equal(actual, [['お金-NEGATION', -1], ['希望-NEGATION', -1], ['喜び-NEGATION', -1]])
actual = a._calc_sentiment_polarity('お金と希望や喜びがない')
assert_equal(actual, [['お金-NEGATION', -1], ['希望-NEGATION', -1], ['喜び-NEGATION', -1]])
actual = a._calc_sentiment_polarity('お金があるじゃない')
assert_equal(actual, [['お金', 1]])
def __init__(self, reload=True, RT_count=3000, print_rep=False):
self.oseti_analyzer = oseti.Analyzer() #極性判定
self.CK = config.CONSUMER_KEY
self.CS = config.CONSUMER_SECRET
self.AT = config.ACCESS_TOKEN
self.AS = config.ACCESS_TOKEN_SECRET
self.ew = "配信スタート ＃キャンペーン リツイートキャンペーン WWWWWWWWW wwwwwwwwww"
self.print_cnt = 0
self.print_rep = print_rep
self.rt = str(RT_count)
self.columns = [
"Id", "Date", "Name", "Full_text", "Judge", "Posi_score",
"Nega_score", "Followers", "link"
]
self.posi_pd = pd.DataFrame([], columns=self.columns)
self.nega_pd = pd.DataFrame([], columns=self.columns)
self.fire_pd = pd.DataFrame([], columns=self.columns)
self.wait = 0
self.reload = reload
day = str(input("ツイートを取得する日付を入力(過去１週間以内/入力形式：YYYY-M-D)："))
day = datetime.strptime(day, '%Y-%m-%d')
self.day = day.strftime('%Y-%m-%d')
#最大2200件のツイートを取得するためのページ
self.pages = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
import seaborn as sns
sns.set(style="whitegrid")
import pandas as pd
import re
import MeCab
from . import make_csv as mc
import codecs
from numpy import mean
import oseti
from . import word_search as ws
from . import jum_analize as jua
import sqlite3
# MeCabインスタンス作成
m = MeCab.Tagger('')
# osetiインスタンス作成
analyzer = oseti.Analyzer()
@login_required
def top_page(request):
user = UserSocialAuth.objects.get(user_id=request.user.id)
#全ツイート取得
mc.mk_twcsv(request)
#csv読み込み
with codecs.open('all_tweets.csv', 'r', 'utf-8', 'ignore') as file:
tw_df = pd.read_csv(file)
#改行を除く
text_list = list(tw_df['tweet_text'])
for i in range(len(text_list)):
text_list[i] = text_list[i].replace('\n', ' ')
def test_split_per_sentence(self):
a = oseti.Analyzer()
actual = a._split_per_sentence('今日は雨。明日は雪?')
assert_equal(len(list(actual)), 2)
def oseti_motivation_score(text):
analyzer = oseti.Analyzer()
score_list = analyzer.analyze(text)
return round(score_list[0], 4)
def tes_oseti():
analyzer = oseti.Analyzer()
score = analyzer.analyze_detail('このイヤホンは重低音が良いです')
print(score)
def __init__(self):
self.analyzer = oseti.Analyzer()
self.evaluate = []
self.sum_posi = 0.0
self.sum_nega = 0.0
def analyze(jeer):
analyzer = oseti.Analyzer()
scores = analyzer.analyze(jeer)
logging.info(scores)
mean_score = mean(scores)
return mean_score
def test_has_arujanai(self):
a = oseti.Analyzer()
actual = a._has_arujanai('やる気あるじゃない')
assert_equal(actual, True)
actual = a._has_arujanai('やる気ないじゃない')
assert_equal(actual, False)