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import csv | |
import time | |
import uuid | |
from pprint import pprint | |
import Pinpoint.FeatureExtraction | |
from Pinpoint.RandomForest import * | |
class predictor(): | |
def __init__(self): | |
self.model = random_forest() | |
self.model.PSYCHOLOGICAL_SIGNALS_ENABLED = False # Needs LIWC markup | |
self.model.BEHAVIOURAL_FEATURES_ENABLED = False | |
self.model.train_model(features_file=None, force_new_dataset=False, | |
model_location=r"far-right-radical-language.model") | |
self.dict_of_users_all = {} | |
self.feature_extractor = Pinpoint.FeatureExtraction.feature_extraction( | |
violent_words_dataset_location="swears", | |
baseline_training_dataset_location="LIWC2015 Results (Storm_Front_Posts).csv") | |
def predict(self, string_to_predict = None, username = "unknown"): | |
if string_to_predict == None: | |
raise Exception("No prediction material given...") | |
extended_prediction_uuid = str(uuid.uuid1())+"-"+str(uuid.uuid1()) | |
self.model.model_folder = "{}-output".format(extended_prediction_uuid) | |
self.feature_extractor.MESSAGE_TMP_CACHE_LOCATION = "{}-message-cache".format(extended_prediction_uuid) | |
print("Starting prediction for {}".format(extended_prediction_uuid)) | |
if string_to_predict != None: | |
users_posts = [{"username": "{}".format(username), "timestamp": "tmp", "message": "{}".format(string_to_predict)}] | |
try: | |
os.remove("./{}-messages.json".format(extended_prediction_uuid)) | |
except: | |
pass | |
with open('{}-all-messages.csv'.format(extended_prediction_uuid), 'w', encoding='utf8', newline='') as output_file: | |
writer = csv.DictWriter(output_file, fieldnames=["username", "timestamp", "message"]) | |
for users_post in users_posts: | |
writer.writerow(users_post) | |
try: | |
self.feature_extractor._get_standard_tweets("{}-all-messages.csv".format(extended_prediction_uuid)) | |
except FileNotFoundError: | |
return False | |
with open("./{}-messages.json".format(extended_prediction_uuid), 'w') as outfile: | |
features = self.feature_extractor.completed_tweet_user_features | |
json.dump(features, outfile, indent=4) | |
rows = self.model.get_features_as_df("./{}-messages.json".format(extended_prediction_uuid), True) | |
rows.pop("is_extremist") | |
try: | |
features = rows.loc[0] | |
is_extremist = self.model.model.predict([features]) | |
except FileNotFoundError as e: | |
is_extremist = False | |
print("Message cache error, next - {}".format(e)) | |
print("Ending prediction for {}".format(extended_prediction_uuid)) | |
dir_name = "." | |
test = os.listdir(dir_name) | |
os.remove("{}-all-messages.csv".format(extended_prediction_uuid)) | |
os.remove("{}-messages.json.csv".format(extended_prediction_uuid)) | |
os.remove("{}-messages.json".format(extended_prediction_uuid)) | |
if is_extremist == True: | |
return True | |
else: | |
return False | |