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| import streamlit as st | |
| import pickle | |
| # Load the trained model | |
| model_filename = 'trained_model.sav' | |
| with open(model_filename, 'rb') as model_file: | |
| model = pickle.load(model_file) | |
| # Load the TF-IDF vectorizer | |
| vectorizer_filename = 'tfidf_vectorizer.sav' | |
| with open(vectorizer_filename, 'rb') as vectorizer_file: | |
| vectorizer = pickle.load(vectorizer_file) | |
| # Define a function to predict cyberbullying and filter bad words | |
| def predict_cyberbullying_and_filter_bad_words(text): | |
| text = text.lower() | |
| # Vectorize the input text using the loaded vectorizer | |
| text_tfidf = vectorizer.transform([text]) | |
| # Use the trained model to make a prediction | |
| prediction = model.predict(text_tfidf) | |
| # Initialize variables to store the filtered text and bad words | |
| filtered_text = text | |
| bad_words = [] | |
| # List of cyberbullying words | |
| cyberbullying_words = ["bitch", "fuck", "asshole", "shitty", "ass", "slut", "cunt", "motherfucker", "wanker", "dick", "shit", "bastard", | |
| "pissed off", "arse", "bugger", "bloody", "whore", "anal", "anus", "arse", "arrse", "assbag", "assbandit", | |
| "assbanger", "assbite", "assclown", "asscock", "asscracker", "asses", "assface", "assfuck", "assfucker", | |
| "assfukka", "assgoblin", "asshat", "asshead", "asshole", "assholes", "asshopper", "assjacker", "asslick", | |
| "asslicker", "assmonkey", "assmunch", "assmuncher", "assnigger", "asspirate", "assshit", "assshole", "asssucker", | |
| "asswad", "asswhole", "asswipe", "auto erotic", "autoerotic", "asswound", "boobs", "bitch", "b1tch", "ballbag", | |
| "balls", "ballsack", "bampot", "bangbros", "bareback", "barely legal", "barenaked", "bastard", "bastardo", "bastinado", | |
| "bbw", "bdsm", "bitches", "bitchin", "bitching", "bitchtits", "bitchy", "blowjob", "boob", "boobs", "booobs", "boooobs", | |
| "booooobs", "booooooobs", "brotherfucker", "bumblefuck", "bung hole", "buttcheeks", "buttfucka", | |
| "buttfucker", "butthole", "buttmuch", "buttplug", "cock", "cocksucker", "camgirl", "camslut", | |
| "camwhore", "circlejerk", "clit", "cleveland steamer", "clit", "clitface", "clitfuck", "clitoris", | |
| "clits", "clover clamps", "clusterfuck", "cockass", "cockbite", "cockburger", "cockeye", "cockface", | |
| "cockfucker", "cockhead", "cockjockey", "cockknoker", "cocklump", "cockmaster", "cockmongler", | |
| "cockmongruel", "cockmonkey", "cockmunch", "cockmuncher", "cocknose", "cocknugget", "cocks", | |
| "cockshit", "cocksmith", "cocksmoke", "cocksmoker", "cocksniffer", "cocksuck", "cocksucked", | |
| "cocksucker", "cocksucking", "cocksucks", "cocksuka", "cocksukka", "cockwaffle", "cok", "cokmuncher", | |
| "coons", "cooter", "coprolagnia", "coprophilia", "cornhole", "creampie", "crotte", "cum", "cumbubble", | |
| "cumdumpster", "cumguzzler", "cumjockey", "cummer", "cumming", "cums", "cumshot", "cumslut", "cumtart", | |
| "cunilingus", "cunillingus", "cunnie", "cunnilingus", "cunt", "cuntass", "cuntface", "cunthole", | |
| "cuntlick", "cuntlicker", "cuntlicking", "cuntrag", "cunts", "cuntslut", "cyalis", "cyberfuc", | |
| "cyberfuck", "cyberfucked", "cyberfucker", "cyberfuckers", "cyberfucking", "d1ck", "darkie", | |
| "date rape", "daterape", "deep throat", "deepthroat", "deggo", "dendrophilia", "dick", "dickbag", | |
| "dickbeaters", "dickface", "dickfuck", "dickfucker", "dickhead", "dickhole", "dickjuice", "dickmilk ", | |
| "dickmonger", "dicks", "dickslap", "dicksucker", "dicksucking", "dicktickler", "dickwad", | |
| "dickweasel", "dickweed", "dickwod", "dike", "dildo", "dildos", "doggystyle ","donkeyribber", | |
| "doochbag", "double dong", "penetration", "doublelift", "douche", "douchebag", "dumbass", | |
| "dumbcunt", "dumbfuck", "ejaculate", "ejaculated", "ejaculates", "ejaculating", "ejaculatings", | |
| "ejaculation", "ejakulate", "erotism", "eunuch", "f u c k", "fagfucker", "fagging", "faggit", | |
| "faggitt", "faggot", "faggotcock", "fanny", "fannyflaps", "fannyfucker", "fanyy", "fatass", "fuck", | |
| "fucker", "fucking", "fecal", "feck", "fecker", "felch", "felching", "fellate", "fellatio", "feltch", | |
| "female squirting", "femdom", "figging", "fingerbang", "fingerfuck", "fingerfucked", "fingerfucker", | |
| "fingerfuckers", "fingerfucking", "fingerfucks", "fingering", "fistfuck", "fistfucked", "fistfucker", | |
| "fistfuckers", "fistfucking", "fistfuckings", "fistfucks", "fisting", | |
| "footjob", "frotting", "fuckass", "fuckbag", "fuckboy", "fuckbrain", "fuckbutt", | |
| "fuckersucker", "fuckface", "fuckhead", "fuckheads", "fuckhole", "fuckin", "fucking", | |
| "fuckings", "fucking shit motherfucker", "fuckme", "fucknut", "fucknutt", "fuckoff", "fucks", | |
| "fuckstick", "fucktard", "fucktards", "fucktart", "fucktwat", "fuckup", "fuckwad", "fuckwhit", | |
| "fuckwit", "fuckwitt", "fudge packer", "fudgepacker", "fuk", "fuker", "fukker", "fukkin", "fuks", | |
| "fukwhit", "fukwit", "futanari", "fux", "fuxor", "g-spot", "gangbang", "gangbanged", "gangbangs", | |
| "gayass", "gaybob", "gaydo", "gayfuck", "gayfuckist", "goregasm", "handjob", "hard core", "hardcore", | |
| "hardcoresex", "hooker", "arse", "ass fuck", "ass hole", "assfucker", "asshole", "assshole", "bastard", | |
| "fucking bitch", "cock", "bloody hell", "boong", "cockfucker", "cocksuck", "coon", "cyberfuck", | |
| "erection", "erotic", "faggot fuck", "fuck off", "fuck you", "fuckass", "fuckhole", "hardcore", | |
| "lesbian", "lesbians", "motherfuck", "negro", "nigger", "orgasim", "orgasm", "penis", "penisfucker", | |
| "piss", "piss off", "pussy", "sexy shit", "sexy slut", "son of a bitch", "suck tits", "xxx", | |
| "kill yourself", "fuck yourself", "beheading", "terrorist"] | |
| # Check for and filter out bad words from the text | |
| for word in cyberbullying_words: | |
| if word.lower() in text: | |
| filtered_text = filtered_text.replace(word, '*' * len(word)) | |
| bad_words.append(word) | |
| # Map the prediction to a human-readable label | |
| return prediction[0], filtered_text, bad_words | |
| # Create a Streamlit app | |
| st.title("Cyberbullying Detection App (English)") | |
| # Add a text input field | |
| user_input = st.text_area("Enter text:", "") | |
| # Predict when a button is clicked | |
| if st.button("Predict"): | |
| if user_input: | |
| prediction, filtered_text, bad_words = predict_cyberbullying_and_filter_bad_words(user_input) | |
| if prediction != "not_cyberbullying": | |
| st.write("Prediction: Cyberbullying") | |
| st.write(f"Cyberbullying Type: {prediction}") | |
| else: | |
| st.write("Prediction: Not Cyberbullying") | |
| if bad_words: | |
| st.write(f"Bad Words: {', '.join(bad_words)}") | |
| else: | |
| st.write("<span style='color:cyan;'>No bad words found.</span>", unsafe_allow_html=True) | |
| if bad_words: | |
| st.write("Filtered Text:") | |
| st.write(f"<span style='color:red; font-weight:bold'>{filtered_text}</span>", unsafe_allow_html=True) | |
| else: | |
| st.write("Original Text:") | |
| st.write(f"{filtered_text}", unsafe_allow_html=True) | |
| st.header("Sample Texts") | |
| st.write("It's always the filthy " + "<span style='color:red; font-weight:bold'>bitch</span> that creates problem between us", unsafe_allow_html=True) | |
| st.write("Do you believe it is appropriate to refer to a Muslim as a " + "<span style='color:red; font-weight:bold'>terrorist</span>?", unsafe_allow_html=True) | |
| st.write("I hope you're doing well and having a great day. Let's catch up soon! 😊") | |
| st.write("The team's score is disgraceful.") | |