import pandas as pd from glob import glob import urllib # format text def clean_text(text): text = text.replace('\n', ' ').replace('\r', ' ').replace('\t', ' ') new_text = [] for t in text.split(): # MAKE SURE to check lowercase t = '@user' if t.startswith('@') and len(t) > 1 and t.replace( '@', '').lower() not in verified_users else t t = '{URL}' if t.startswith('http') else t new_text.append(t) return ' '.join(new_text) # test set with open('./SemEval2017-task4-test.subtask-CE.english.txt') as f: test_lines = f.readlines() test = [x.split('\t') for x in test_lines] test = pd.DataFrame(test, columns=['id', 'topic', 'gold_label', 'text']) # validation set fnames = ['twitter-2016dev-CE.txt', 'twitter-2016devtest-CE.txt'] validation_lines = [] for input_f in fnames: with open(input_f) as f: lines = f.readlines() validation_lines.extend(lines) validation = [x.split('\t') for x in validation_lines] validation = pd.DataFrame( validation, columns=['id', 'topic', 'gold_label', 'text']) # train set fnames = ['./twitter-2016train-CE.txt', './twitter-2016test-CE.txt'] train_lines = [] for input_f in fnames: with open(input_f) as f: lines = f.readlines() train_lines.extend(lines) train = [x.split('\t') for x in train_lines] train = pd.DataFrame( train, columns=['id', 'topic', 'gold_label', 'text']) # clean text verified_users = urllib.request.urlopen( 'https://raw.githubusercontent.com/cardiffnlp/timelms/main/data/verified_users.v091122.txt').readlines() verified_users = [x.decode().strip('\n').lower() for x in verified_users] train['text'] = train['text'].apply(clean_text) validation['text'] = validation['text'].apply(clean_text) test['text'] = test['text'].apply(clean_text) # map classes to 0-4 class_map = { -2:0, -1:1, 0:2, 1:3, 2:4 } train['gold_label'] = train['gold_label'].map(class_map) validation['gold_label'] = validation['gold_label'].map(class_map) test['gold_label'] = test['gold_label'].map(class_map) # save splits cols_to_keep = ['gold_label', 'topic', 'text'] train[cols_to_keep].to_json( '../data/tweet_sentiment/train.jsonl', lines=True, orient='records') validation[cols_to_keep].to_json( '../data/tweet_sentiment/validation.jsonl', lines=True, orient='records') test[cols_to_keep].to_json( '../data/tweet_sentiment/test.jsonl', lines=True, orient='records')