def getHapinessScoreTextWithOutEmoji(tweet_text):
global file
file = pyhmeter.load_scores()
py = getPyhmeter(tweet_text)
score = py.happiness_score()
file = pyhmeter.load_scores_emoji()
py3 = getPyhmeter(tweet_text)
if score != None and len(py3.matchlist) == 0:
#print(tweet_text)
return score
return -1
def getHapinessScoreTextWithEmojiRemoved(tweet_text):
global file
file = pyhmeter.load_scores()
py = getPyhmeter(tweet_text)
score = py.happiness_score()
file = pyhmeter.load_scores_word()
py2 = getPyhmeter(tweet_text)
score2 = py2.happiness_score()
file = pyhmeter.load_scores_emoji()
py3 = getPyhmeter(tweet_text)
score3 = py2.happiness_score()
if score != None and score2 != None and len(py3.matchlist) != 0:
#print(tweet_text)
return score2
return -1
from nltk.tokenize import TweetTokenizer
import pyhmeter
import re
from heapq import nlargest, nsmallest
from operator import itemgetter
import configscript
import tweepy as tw
import pandas as pd
from sqlalchemy import create_engine
import matplotlib.pyplot as plt
from scipy.stats import kde
import seaborn as sns
from decouple import config
engine = create_engine(config('POSTGRESS'))
file = pyhmeter.load_scores()
# Gets the Pyhmeter and removes unnecessary symbols from a given tweet
def getPyhmeter(tweet_text):
#TODO: remove URL and other stuff to clean text
pattern = re.compile('(@\w*)|(\|.*)|(#\s*)')
removedAt = pattern.sub('', tweet_text)
tk = TweetTokenizer()
tokens = tk.tokenize(removedAt)
return pyhmeter.HMeter(tokens, file, 1)
# Gets the happiness score from a single tweet
def getHapinessScoreTextWithEmoji(tweet_text):
def setUp(self):
self.doddscores = pyhmeter.load_scores("Data_Set_S1.txt")
def main():
def printTweet(descr, t):
print(descr)
print("Username: %s" % t.username)
print("Retweets: %d" % t.retweets)
print("Text: %s" % t.text)
print("Mentions: %s" % t.mentions)
print("Hashtags: %s\n" % t.hashtags)
data = pd.read_csv(os.getcwd() + "/followers.txt", header=None)
# print(data[0])
sample_scores = pyhmeter.load_scores("Data_Set_S1.txt")
scores = []
dates = []
cnt = 0
average_score = 0
for month in ["%.2d" % i for i in range(1, 13)]:
monthly_score = 0
user_cnt = 0
cnt = 0
for user in data[0].sample(n=2000):
tweetCriteria = got.manager.TweetCriteria().setUsername(
user).setQuerySearch("ClimateChange").setSince(
"2019-" + month + "-01").setUntil("2019-" + month +
"-30").setMaxTweets(10)
# sum=0
# cnt=0
for i in got.manager.TweetManager.getTweets(tweetCriteria):
# printTweet("### Example 1 - Get tweets by username [barackobama]", i)
user_cnt += 1
h = pyhmeter.HMeter(list((i.text).split()), sample_scores)
if h.happiness_score() is not None:
monthly_score += h.happiness_score()
print(cnt)
cnt += 1
print(user)
print(h.happiness_score())
# dates.append(i.date)
# print(i.date)
# l.append(h.happiness_score())
# print(h.happiness_score())
if cnt != 0:
# monthly_score+=sum
monthly_score /= cnt
print(monthly_score)
scores.append(monthly_score)
average_score += monthly_score
dates.append(month)
# datetimes=matplotlib.dates.date2num(dates)
# plt.plot_date(datetimes,scores,marker=None,linestyle="-")
average_score /= len(scores)
print(scores, dates)
plt.plot(dates, scores, label="actual data", color="red")
plt.axhline(y=average_score, label="average score")
# plt.plot(average_score)
plt.xticks(rotation=70)
plt.xlabel("time(month)")
plt.ylabel("hedonometer score")
plt.legend()
# plt.title("")
plt.savefig(
"/home/saksham/Twitter_Project/GetOldTweets-python-master/test3.png")
plt.show()
def main():
def printTweet(descr, t):
print(descr)
print("Username: %s" % t.username)
print("Retweets: %d" % t.retweets)
print("Text: %s" % t.text)
print("Mentions: %s" % t.mentions)
print("Hashtags: %s\n" % t.hashtags)
# data=pd.read_csv(os.getcwd()+"/followers.csv")
# # print(data)
# l=[]
# print(data["screen_name"][0][35:(len(data["screen_name"][0])-(len(data["screen_name"][0])-36)/2)-4])
# # print(data["screen_name"][1])
# f=open(os.getcwd()+"/followers.txt","a")
# for i in range(len(data["screen_name"])):
# f.write(data["screen_name"][i][35:(len(data["screen_name"][i])-(len(data["screen_name"][i])-36)/2)-4]+"\n")
# l.append(data["screen_name"][i][35:(len(data["screen_name"][i])-(len(data["screen_name"][i])-36)/2)-4])
# # print(l)
data = pd.read_csv(os.getcwd() + "/followers.txt", header=None)
# print(data[0])
sample_scores = pyhmeter.load_scores("Data_Set_S1.txt")
scores = []
dates = []
days = ["%.2d" % i for i in range(1, 30)]
cnt = 0
for month in ["%.2d" % i for i in range(1, 13)]:
for day in range(len(days) - 1):
date = "2019-" + str(month) + "-" + str(days[day])
next_date = "2019-" + str(month) + "-" + str(days[day + 1])
day_score = 0
for user in data[0][:100]:
print("querying...")
cnt += 1
print(cnt)
tweetCriteria = got.manager.TweetCriteria().setUsername(
user).setQuerySearch("ClimateChange").setSince(
date).setUntil(next_date).setMaxTweets(1)
sum = 0
for i in got.manager.TweetManager.getTweets(tweetCriteria):
# printTweet("### Example 1 - Get tweets by username [barackobama]", i)
h = pyhmeter.HMeter(list((i.text).split()), sample_scores)
sum += h.happiness_score()
# dates.append(i.date)
# print(i.date)
# l.append(h.happiness_score())
# print(h.happiness_score())
# cnt+=1
# print(cnt)
sum /= i
day_score += sum
day_score /= 100
dates.append(date)
scores.append(day_score)
datetimes = matplotlib.dates.date2num(dates)
plt.plot_date(datetimes, scores, marker=None, linestyle="-")
plt.xticks(rotation=70)
plt.xlabel("time")
plt.ylabel("hedonometer score")
plt.savefig(
"/home/saksham/Twitter_Project/GetOldTweets-python-master/test3.png")
plt.show()
# coding: utf-8
import pyhmeter
import got
import matplotlib.pyplot as plt
import sys
import matplotlib
import pandas as pd
import os
import re
sample_scores = pyhmeter.load_scores("Data_Set_S1.txt")
scores = []
dates = []
tweets = []
url_rem = []
neutral_rem = []
normal = []
url_score = []
neutral_score = []
# tweetCriteria=got.manager.TweetCriteria().setUsername("barackobama").setQuerySearch("ClimateChange").setSince('2019-03-01').setUntil('2019-12-30').setMaxTweets(10000)
tweetCriteria = got.manager.TweetCriteria().setUsername(
"KremlinRussia_E").setQuerySearch("Climate").setSince(
"2009-12-30").setUntil("2019-12-30").setMaxTweets(100000)
print(got.manager.TweetManager.getTweets(tweetCriteria))
for i in got.manager.TweetManager.getTweets(tweetCriteria):
text = re.sub(r'[^\x00-\x7F]+', ' ', i.text)
tweets.append(text)
h = pyhmeter.HMeter(list(i.text.split()), sample_scores)
normal.append(h.happiness_score())
h.deltah = 1.0
neutral_score.append(h.happiness_score())