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# preprocessing\n\n # emoticon analysis\n all_emoticons = \n\n def get_emoticons ( tokens ):\n emoticons = \n\n for token in tokens :\n for i in range ( len ( all_emoticons )):\n if token in all_emoticons :\n emoticons.
![des mein nikla hoga chand episode 159 des mein nikla hoga chand episode 159](https://m.media-amazon.com/images/M/MV5BYzg0ZDc2ZmItYjljYi00MWI0LWE2MGYtODRiNDBjNGJiZmQ0XkEyXkFqcGdeQXVyNzM4MjU3NzY@._V1_.jpg)
\n [Na, afsos, hai, tujhe, sahab, na, koi, sharmi. \n Na afsos hai tujhe sahab na koi sharmindagi ha. \n [Dekho,, tum, gambhir, majaak, kar, rahe, ho. \n Dekho, tum gambhir majaak kar rahe ho #Irony \n [rest, hi, hi, hi, en, en, hi, hi, en, rest, r. \n [4, dinn, ki, chutti, and, month, bhar, ka, ho. \n 4 dinn ki chutti and month bhar ka homework. \n [hi, en, en, hi, rest, hi, hi, hi, hi, hi, hi. \n [I, sing, this, in, #sarcasm:, Mujhe, tum, se. \n I sing this in #sarcasm: Mujhe tum se pyar nah. \n [hi, hi, hi, en, rest, en, hi, hi, hi, hi, hi. \n [Aaj, dhoni, ko, god,, magic, man, bolnewale. \n Aaj dhoni ko god, magic man bolnewale kabhi us.
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\n [rest, hi, hi, hi, hi, hi, hi, hi, hi, hi, res. \n [hi, rest, hi, rest, hi, rest, hi, rest, hi, r. \n [kaafiron, ', ko, ', masjid, ', mein, ', namaz. \n kaafiron' ko 'masjid' mein 'namaz' perhtay hua. \n [hi, en, hi, hi, en, en, hi, hi, rest, hi, hi. \n [Abusing, tweet, ke, liye, Account, suspend, k. \n Abusing tweet ke liye Account suspend karte ho. \n [rest, hi, hi, hi, rest, hi, hi, hi, rest, hi.ĥ250 rows × 5 columns\n\n\n\n\n\n\n\n\n\n \n [rest, hi, rest, hi, hi, en, hi, hi, rest, hi. \n [rest, hi, rest, hi, hi, hi, hi, hi, hi, hi, h. \n [hi, hi, rest, hi, hi, en, hi, hi, rest, hi, e. \n [Khiladi, anari,, aur, shaamat, equipment, k. \n Khiladi anari, aur shaamat equipment ki aye! B. \n [rest, hi, hi, hi, hi, en, hi, hi, hi, hi, hi. \n [#RememberingRajiv, aaj, agar, musalman, aurat. \n #RememberingRajiv aaj agar musalman auraten tr. \n [hi, hi, rest, hi, hi, hi, rest, hi, en, hi, h. \n [hi, hi, hi, hi, hi, hi, hi, rest, hi, hi, hi. \n [Hindu, baheno, par, julam, bardas, nahi, hoga. \n Hindu baheno par julam bardas nahi hoga NO \n [hi, hi, hi, en, hi, hi, hi, en, hi, en, hi, h. \n [Batao, ye, uss, site, pr, se, akki, sir, ke. \n Batao ye uss site pr se akki sir ke verdict ni. \n Triple Talaq par Burbak Kuchh nahi bolega append ( languages )\n tokens = \n languages = \n elif len ( line ) = 1 :\n continue\n else :\n tokens. ' ]\n if len ( line ) = 0 :\n tokens_list. strip () for token in line if token != '' and token != ' ' and token != ' append ( lines1 )\n\n\n # tweets with language\n f2 = open ( '/content/drive/My Drive/Data Files/code-mixed analysis data/Sarcasm_tweets_with_language.txt', 'r' )\n tokens_list = \n tokens = \n languages_list = \n languages = \n for line in f2 :\n line = line. append ( new_lines )\n\n\n # annotations\n with open ( '/content/drive/My Drive/Data Files/code-mixed analysis data/Sarcasm_tweet_truth.txt' ) as f1 :\n lines1 = \n\n labels = \n\n for i in range ( len ( lines1 )):\n if i % 2 != 0:\n labels.
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append ( line )\n\n tweet_ids = \n tweets = \n\n for i in range ( len ( new_lines )):\n if i % 2 = 0:\n tweet_ids. # sarcasm data\n with open ( '/content/drive/My Drive/Data Files/code-mixed analysis data/Sarcasm_tweets.txt' ) as f :\n lines = \n\n new_lines = \n for line in lines :\n if line = '' :\n continue\n new_lines.