def tweet_download_and_lang_detect(df_tweets, user_id,
update_to_invalid_list):
"""
Calls language detection and checks if enough german tweets remain.
If it found almost enough german Tweets it will load more.
If it found almost none it will abort.
:param df_tweets: 0 during first run, dataframe with tweets during later runs
:param user_id: Twitter User_ID for tweet download and language check
:param update_to_invalid_list: List of user that can not be downloaded from. Will append to if applicable.
:return: df_tweets, update_to_invalid_list, abort_loop, len_df
"""
if isinstance(df_tweets, int):
df_tweets = TwitterAPI.API_tweet_multitool(
user_id,
'temp',
pages=1,
method='user_timeline',
append=False,
write_to_db=False) # fills DF with 200 tweets of 1 page
df_tweets = helper_functions.lang_detect(df_tweets)
else:
df_tweets_additions = TwitterAPI.API_tweet_multitool(
user_id,
'temp',
pages=1,
method='user_timeline',
append=False,
write_to_db=False) # fills DF with 200 tweets of 1 page
df_tweets_additions = helper_functions.lang_detect(
df_tweets_additions)
if isinstance(df_tweets_additions, pd.DataFrame):
df_tweets = pd.concat([df_tweets, df_tweets_additions])
df_tweets.reset_index(inplace=True)
del df_tweets['index']
# if df_tweets is None: #no tweets found or all tweets deleted (non german)
# abort_loop = True
# return df_tweets, update_to_invalid_list, abort_loop'
len_df = helper_functions.dataframe_length(df_tweets)
if len_df <= 50:
# if almost no tweets are german don't try to get more german tweets from this users.
# would take to many page loads
update_to_invalid_list.append(user_id)
abort_loop = True
elif len_df >= 200:
abort_loop = True
else:
# if to few tweets are german load more tweets to get a better result
abort_loop = False
gc.collect()
return df_tweets, update_to_invalid_list, abort_loop, len_df
def download_user_timelines(political_moderate_list: list,
right_wing_populists_list: list):
"""
Downloads user timelines of users featured in below lists. The downloads are used as training material for AI
training. All lists are just incomplete examples.
:return:
"""
#List examples
# political_moderate_list = ['_pik_dame_', 'Leekleinkunst', 'MartinaKraus7', 'KAFVKA', 'Volksverpetzer', 'insideX',
# 'FranziLucke', 'leonie_stella9', 'Ute631', 'justMPO', 'anouk_avf', 'Komisaar',
# 'MenschBernd', 'von_ems', 'lies_das', 'seewanda', 'Rene_Bacher', 'Prasanita93',
# 'IgorUllrich', 'AJSalzgitter', 'Bussi72', 'HuWutze', 'strahlgewitter', 'PhilKupi',
# 'BaldusEla', 'LarsKlingenberg', 'MichaelSchfer71', 'EddyAges', 'veripot', 'JoernPL',
# 'ondreka', 'kleinerJedi', 'DanielKinski', 'wfh7175', 'Sister_records1', 'TinaJergerkamp']
# right_wing_populists_list = ['Junge_Freiheit', 'zaferflocken', 'HelmutWachler', 'M_Briefing', 'TinVonWo', 'mcwd12',
# 'EBlume3', 'h_hendrich']
#Political unpolitical stance is currently not used
# Tweets of below accounts will be downloaded from twitter. During model a subset of below accounts might be used.
# unpolitical_list = ['Podolski10', 'fckoeln', 'FCBayern', 'BVB', 'rtl2', 'DMAX_TV', 'tim_kocht', 'grandcheflafer',
# 'bildderfrau', 'gala', 'BUNTE', 'promiflash', 'funny_catvideos', 'BibisBeauty', 'dagibee',
# 'siggismallz', 'Gronkh', 'CHIP_online', 'COMPUTERWOCHE', 'SkySportNewsHD', 'MOpdenhoevel',
# 'kayefofficial', 'VOGUE_Germany', 'lucycatofficial', 'RealLexyRoxx', 'AnselmSchindler',
# 'pentru_tine', 'KaJa80028344']
#unpolitical_list = ['Podolski10'] For Testing
# political_list = ['Thomas_Ehrhorn', 'HilseMdb', 'DirkSpaniel', 'MdB_Lucassen', 'RolandTichy', 'UllmannMdB',
# 'c_jung77', 'michael_g_link', 'theliberalfrank', 'IreneMihalic', 'KaiGehring', 'RenateKuenast',
# 'GoeringEckardt', 'MdB_Freihold', 'ZaklinNastic', 'PetraPauMaHe', 'lgbeutin', 'arnoklare',
# 'zierke', 'Timon_Gremmels', 'Johann_Saathoff', 'uhl_markus', 'AnjaKarliczek', 'KLeikert',
# 'Junge_Gruppe']
user_lists = {
'political_moderate_list': political_moderate_list,
'right_wing_populists_list': right_wing_populists_list
}
# List Download
for list_name, username_list in user_lists.items():
for element in username_list:
TwitterAPI.API_tweet_multitool(element,
list_name,
pages=10,
method='user_timeline',
append=True,
write_to_db=True)
def eval_bert(model_path) -> None:
"""
Runs evaluation against evaluation accounts in table "eval_table"
Return a printout of the results
:return: none
"""
data = []
df_pred_data = pd.DataFrame(data,
columns=[
'screen_name', 'pol', 'unpol', 'pol_time',
'left', 'right', 'lr_time'
])
sql = "select distinct username from eval_table"
#sql = "select distinct screen_name as username from n_users where id = 805308596"
df = db_functions.select_from_db(sql)
print("Loading BERT")
# older version
# model_path = r"C:\Users\Admin\PycharmProjects\untitled\outputs\political_bert_1605094936.6519241\checkpoint-15000"
# model_path = r"F:\AI\outputs\political_bert_1605652513.149895\checkpoint-480000"
model = init(model_path)
print("Querying BERT")
for index, element in tqdm(df.iterrows(), total=df.shape[0]):
screen_name = element[0]
df_tweets = TwitterAPI.API_tweet_multitool(
screen_name,
'temp',
pages=1,
method='user_timeline',
append=False,
write_to_db=False) # speichert tweets in DF
if isinstance(
df_tweets,
str): # if df_tweets is a string it contains an error message
continue
start_time = time.time()
german_language = helper_functions.lang_detect(df_tweets)
runtime = time.time() - start_time
print(f"Runtime Lang Detect: {runtime}")
if german_language is False:
continue
start_time = time.time()
prediction_result = [bert_predictions(df_tweets['tweet'], model)]
runtime = time.time() - start_time
print(f"Runtime Bert: {runtime}")
result = prediction_result[0]
df_pred_data.at[index, 'screen_name'] = screen_name
try:
df_pred_data.at[index, 'left'] = result[0]
df_pred_data.at[index, 'right'] = result[1]
except:
df_pred_data.at[index, 'left'] = 0
df_pred_data.at[index, 'right'] = 0
df_pred_data.at[index, 'lr_time'] = runtime
print("screen_name,Pol,Unpol,Pol_Time,Left,Right,LR_Time")
for index, element in df_pred_data.iterrows():
print(
f"{element['screen_name']},{element['pol']},{element['unpol']},{element['pol_time']},{element['left']},"
f"{element['right']},{int(element['lr_time'])}")
