y_other = []
text_other = []
x_all = []
y_all = []
x_male = []
y_male = []
text_male = []
x_female = []
y_female = []
text_female = []
for handle, magnitude in dictionaryByValue(tweet_density):
subject = get_values(handle=handle)[0]
print(subject['name'])
x_all.append(magnitude)
y_all.append(deleted_density[handle])
if subject['sex'] == 'male':
text_male.append(subject['name'])
x_male.append(magnitude)
y_male.append(deleted_density[handle])
else:
text_female.append(subject['name'])
x_female.append(magnitude)
y_female.append(deleted_density[handle])
my_suspended_deleted_list = []
subjects_dict = {}
stance_count = {}
with open('closed_accounts.txt', mode='r') as fs:
for account in fs:
my_deleted_list.append(account.strip().lower())
my_suspended_deleted_list.append(account.strip().lower())
with open('suspended.txt', mode='r') as fs:
for account in fs:
my_suspended_list.append(account.strip().lower())
my_suspended_deleted_list.append(account.strip().lower())
# get political stance for all Twitter observed accounts
for account in get_values():
subjects_dict[account['handle'].lower()] = {'stance': account['stance']}
if account['stance'] not in stance_count:
stance_count[account['stance']] = 1
else:
stance_count[account['stance']] += 1
max_density = 0
handle_max_density = ''
is_tweet_density = True
appearance = {}
print(
observed.handle_text_conversation_replies('iamsambee',
'885869337063686144',
'camarogirl91'))
import numpy as np
import plotly
from twitter_apps.Subjects import get_values
plotly.offline.init_notebook_mode(connected=True)
with open('data/account_features.pkl', mode='rb') as fhd:
obj = pickle.load(fhd)
x = list(range(1, len(obj) + 1))
y = []
text = []
values = []
for account in obj:
subject = get_values(handle=account)[0]
print(subject['name'])
print(
'User-name: {}, Number of appearances across conversations: {}, Ave. appearances across conversations: {}'
.format(account, obj[account]['appearance-across-conversation-count'],
obj[account]['ave-handle-appearance-across-conversation']))
values.append((obj[account]['appearance-across-conversation-count'],
subject['name']))
#for feature in obj[account]:
# print('\t{}: {}'.format(feature, obj[account]['ave-handle-appearance-across-conversation']))
print(len(obj))
my_suspended_deleted_list = []
subjects_dict = {}
stance_count = {}
with open('closed_accounts.txt', mode='r') as fs:
for account in fs:
my_deleted_list.append(account.strip().lower())
my_suspended_deleted_list.append(account.strip().lower())
with open('suspended.txt', mode='r') as fs:
for account in fs:
my_suspended_list.append(account.strip().lower())
my_suspended_deleted_list.append(account.strip().lower())
# get political stance for all Twitter observed accounts
for account in get_values():
subjects_dict[account['handle'].lower()] = {'stance': account['stance']}
if account['stance'] not in stance_count:
stance_count[account['stance']] = 1
else:
stance_count[account['stance']] += 1
max_density = 0
handle_max_density = ''
is_tweet_density = True
appearance = {}
total_number_tweets = 0
total_number_handles = 0
total_number_conversations = 0
total_number_handles_in_conversation = 0
my_suspended_deleted_list = []
subjects_dict = {}
stance_count = {}
with open('closed_accounts.txt', mode='r') as fs:
for account in fs:
my_deleted_list.append(account.strip().lower())
my_suspended_deleted_list.append(account.strip().lower())
with open('suspended.txt', mode='r') as fs:
for account in fs:
my_suspended_list.append(account.strip().lower())
my_suspended_deleted_list.append(account.strip().lower())
# get political stance for all Twitter observed accounts
for account in get_values():
subjects_dict[account['handle'].lower()] = {'stance': account['stance']}
if account['stance'] not in stance_count:
stance_count[account['stance']] = 1
else:
stance_count[account['stance']] += 1
max_density = 0
handle_max_density = ''
is_tweet_density = True
appearance = {}
print(
observed.handle_text_conversation_replies('iamsambee',
'885869337063686144',
'camarogirl91'))
from twitter_apps.Subjects import get_values
from twitter_apps.TwitterFunctions import TwitterObject
all_handles = []
for account in get_values():
print(account['handle'])
all_handles.append(account['handle'])
my_api = TwitterObject()
user_ids = my_api.api.lookup_users(screen_names=all_handles[:100])
for user in user_ids:
print(user.screen_name, user.id)
user_ids = my_api.api.lookup_users(screen_names=all_handles[100:])
print()
print(all_handles[99:105])
print()
for user in user_ids:
print(user.screen_name, user.id)
y4 = []
text5 = []
x5 = []
y5 = []
with open('closed_accounts.txt', mode='r') as fs:
for account in fs:
my_deleted_list.append(account.strip().lower())
my_suspended_deleted_list.append(account.strip().lower())
with open('suspended.txt', mode='r') as fs:
for account in fs:
my_suspended_list.append(account.strip().lower())
my_suspended_deleted_list.append(account.strip().lower())
for current_handle in get_values():
del_rows, all_handles = observed.handle_conversation_matrix(
current_handle['handle'], my_suspended_deleted_list)
all_rows = observed.handle_conversations_id(current_handle['handle'])
deleted_amount[current_handle['handle']] = 0
for row in del_rows:
for handle in row[list(row)[0]]:
deleted_amount[current_handle['handle']] += row[list(row)
[0]][handle]
deleted_percent = len(del_rows) / len(all_rows)
deleted_data[current_handle['handle']] = deleted_percent
subjects_dict[current_handle['handle']] = current_handle['name']
print(deleted_amount[current_handle['handle']])