Yavuz Kömeçoğlu yavuzKomecoglu

## twitter_sentiment_analysis_emmys2022_generate_word_cloud_from_frequencies.py
from wordcloud import WordCloud

def generate_word_cloud_from_frequencies(freq_dict, status):

    wordcloud = WordCloud(
        width=800,
        height=400,
        background_color = 'black',
        stopwords = stop_words).generate_from_frequencies(frequencies=freq_dict)


## twitter_sentiment_analysis_emmys2022_preprocess_tweet.py
def preprocess_tweet(tweet):
    processed_tweet = []
    # Convert to lower case
    tweet = tweet.lower()

    #Clean only digits
    tweet = re.sub("^\d+\s|\s\d+\s|\s\d+$", " ", tweet)

    # Replaces URLs with the word URL
    #tweet = re.sub(r'((www\.[\S]+)|(https?://[\S]+))', ' URL ', tweet)

## twitter_sentiment_analysis_emmys2022_preprocess_emoji.py
def handle_emojis(tweet):
    # Smile -- :), : ), :-), (:, ( :, (-:, :')
    tweet = re.sub(r'(:\s?\)|:-\)|\(\s?:|\(-:|:\'\))', ' EMO_POS ', tweet)
    # Laugh -- :D, : D, :-D, xD, x-D, XD, X-D
    tweet = re.sub(r'(:\s?D|:-D|x-?D|X-?D)', ' EMO_POS ', tweet)
    # Love -- <3, :*
    tweet = re.sub(r'(<3|:\*)', ' EMO_POS ', tweet)
    # Wink -- ;-), ;), ;-D, ;D, (;,  (-;
    tweet = re.sub(r'(;-?\)|;-?D|\(-?;)|😉', ' EMO_POS ', tweet)
    # Sad -- :-(, : (, :(, ):, )-:

## twitter_sentiment_analysis_emmys2022_preprocess_word.py
def preprocess_word(word):
  # Remove punctuation
  word = word.strip('\'"?!,.():;``')

  # Convert more than 2 letter repetitions to 2 letter
  # funnnnny --> funny
  word = re.sub(r'(.)\1+', r'\1\1', word)
  # Remove - & '
  word = re.sub(r'(-|\')', '', word)
  return word

## twitter_sentiment_analysis_emmys2022_import_model_and_pipeline_for_transformens.py
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
# load model
model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
# create pipeline
sa = pipeline("sentiment-analysis", tokenizer=tokenizer, model=model)

## twitter_sentiment_analysis_emmys2022_search_query_for_snscrape.py
import snscrape.modules.twitter as sntwitter
import pandas as pd

def search_hashtag(searchterm, dt_until, dt_since, lang, limit=100000):
    query = "({searchterm}) lang:{lang} until:{until} since:{since}".format(searchterm=searchterm, lang=lang, until=dt_until, since=dt_since)
    #query = (#Emmys2022) lang:en until:2022-09-14 since:2022-09-01

    tweets = []
    limit = limit


## turkey_county_neighborhoods.json
{
  "adana": [
    "Hatay",
    "Osmaniye",
    "Kahramanmaras",
    "Kayseri",
    "Nigde",
    "Mersin"
  ],
  "adiyaman": [

## check_youtube_channel_is_live.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-

#Sample use: $ python3 test_youtube_live.py -c "UCryGec9PdUCLjpJW2mgCuLw"
# {'video_id': 'j78TwQCfEzc', 'video_link': 'https://www.youtube.com/watch?v=j78TwQCfEzc', 'published_at': '2019-11-14T03:13:53.000Z', 'title': 'Seeing 2020', 'isLive': True}
import argparse
import requests
import json

ap = argparse.ArgumentParser()

## intenseye-detection-api.py
import requests
import json

API_URL = 'https://api.intenseye.com/images/detection'
TOKEN = '{INTENSEYE_TOKEN}'

IMAGE_URL = "http://yavuzkomecoglu.com/img/hababam.jpg"

headers = {
  'Content-Type': 'application/json'

## intenseye-detection-api-draw.py
from PIL import Image
from io import BytesIO
import numpy as np
import requests
import json
import cv2

TOKEN = '{INTENSEYE_TOKEN}'
IMAGE_URL = "http://yavuzkomecoglu.com/img/hababam.jpg"
	from wordcloud import WordCloud

	def generate_word_cloud_from_frequencies(freq_dict, status):

	wordcloud = WordCloud(
	width=800,
	height=400,
	background_color = 'black',
	stopwords = stop_words).generate_from_frequencies(frequencies=freq_dict)
	def preprocess_tweet(tweet):
	processed_tweet = []
	# Convert to lower case
	tweet = tweet.lower()

	#Clean only digits
	tweet = re.sub("^\d+\s\|\s\d+\s\|\s\d+$", " ", tweet)

	# Replaces URLs with the word URL
	#tweet = re.sub(r'((www\.[\S]+)\|(https?://[\S]+))', ' URL ', tweet)
	def handle_emojis(tweet):
	# Smile -- :), : ), :-), (:, ( :, (-:, :')
	tweet = re.sub(r'(:\s?\)\|:-\)\|\(\s?:\|\(-:\|:\'\))', ' EMO_POS ', tweet)
	# Laugh -- :D, : D, :-D, xD, x-D, XD, X-D
	tweet = re.sub(r'(:\s?D\|:-D\|x-?D\|X-?D)', ' EMO_POS ', tweet)
	# Love -- <3, :*
	tweet = re.sub(r'(<3\|:\*)', ' EMO_POS ', tweet)
	# Wink -- ;-), ;), ;-D, ;D, (;, (-;
	tweet = re.sub(r'(;-?\)\|;-?D\|\(-?;)\|😉', ' EMO_POS ', tweet)
	# Sad -- :-(, : (, :(, ):, )-:
	def preprocess_word(word):
	# Remove punctuation
	word = word.strip('\'"?!,.():;``')

	# Convert more than 2 letter repetitions to 2 letter
	# funnnnny --> funny
	word = re.sub(r'(.)\1+', r'\1\1', word)
	# Remove - & '
	word = re.sub(r'(-\|\')', '', word)
	return word
	from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
	# load model
	model = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
	tokenizer = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
	# create pipeline
	sa = pipeline("sentiment-analysis", tokenizer=tokenizer, model=model)
	import snscrape.modules.twitter as sntwitter
	import pandas as pd

	def search_hashtag(searchterm, dt_until, dt_since, lang, limit=100000):
	query = "({searchterm}) lang:{lang} until:{until} since:{since}".format(searchterm=searchterm, lang=lang, until=dt_until, since=dt_since)
	#query = (#Emmys2022) lang:en until:2022-09-14 since:2022-09-01

	tweets = []
	limit = limit
	{
	"adana": [
	"Hatay",
	"Osmaniye",
	"Kahramanmaras",
	"Kayseri",
	"Nigde",
	"Mersin"
	],
	"adiyaman": [
	#!/usr/bin/env python
	# -- coding: utf-8 --

	#Sample use: $ python3 test_youtube_live.py -c "UCryGec9PdUCLjpJW2mgCuLw"
	# {'video_id': 'j78TwQCfEzc', 'video_link': 'https://www.youtube.com/watch?v=j78TwQCfEzc', 'published_at': '2019-11-14T03:13:53.000Z', 'title': 'Seeing 2020', 'isLive': True}
	import argparse
	import requests
	import json

	ap = argparse.ArgumentParser()
	import requests
	import json

	API_URL = 'https://api.intenseye.com/images/detection'
	TOKEN = '{INTENSEYE_TOKEN}'

	IMAGE_URL = "http://yavuzkomecoglu.com/img/hababam.jpg"

	headers = {
	'Content-Type': 'application/json'
	from PIL import Image
	from io import BytesIO
	import numpy as np
	import requests
	import json
	import cv2

	TOKEN = '{INTENSEYE_TOKEN}'
	IMAGE_URL = "http://yavuzkomecoglu.com/img/hababam.jpg"