{"id":27446299,"url":"https://github.com/anastasius21/fakenewsmodel","last_synced_at":"2026-05-05T00:36:31.880Z","repository":{"id":287936104,"uuid":"966293613","full_name":"anastasius21/FakeNewsModel","owner":"anastasius21","description":"The repo contains the model for fake news detection and a streamlit app for its implementation.","archived":false,"fork":false,"pushed_at":"2025-04-14T18:43:27.000Z","size":14,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-15T04:15:30.468Z","etag":null,"topics":["fake-news-detection","machine-learning","nlp","pandas","python","scikit-learn"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/anastasius21.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-04-14T17:45:14.000Z","updated_at":"2025-04-14T18:43:31.000Z","dependencies_parsed_at":"2025-04-14T18:57:59.870Z","dependency_job_id":null,"html_url":"https://github.com/anastasius21/FakeNewsModel","commit_stats":null,"previous_names":["anastasius21/fakenewsmodel"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anastasius21%2FFakeNewsModel","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anastasius21%2FFakeNewsModel/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anastasius21%2FFakeNewsModel/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/anastasius21%2FFakeNewsModel/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/anastasius21","download_url":"https://codeload.github.com/anastasius21/FakeNewsModel/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249003963,"owners_count":21196793,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["fake-news-detection","machine-learning","nlp","pandas","python","scikit-learn"],"created_at":"2025-04-15T04:15:38.451Z","updated_at":"2026-05-05T00:36:31.832Z","avatar_url":"https://github.com/anastasius21.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 📰 Fake News Detection using NLP \u0026 Streamlit\nThis project focuses on detecting fake news articles using Natural Language Processing (NLP) and Machine Learning. It includes both model training in Jupyter Notebook and a simple Streamlit app for interactive prediction.\nDataset: https://www.kaggle.com/c/fake-news/data\n\n# Overview\nThis project focuses on building a binary classifier that uses text features from news articles to determine their authenticity.\n\nThe core workflow includes:\n\nPreprocessing and cleaning text data.\n\nConverting text into numerical features using TF-IDF.\n\nTraining a Decision Tree model to classify content as reliable or unreliable.\n\nDeploying the model using Streamlit to make it accessible and interactive.\n\n# 🧠 Features \u0026 Highlights\n\n✔ End-to-end preprocessing pipeline using NLTK\n\n✔ TF-IDF Vectorization for feature extraction\n\n✔ Trained using a Decision Tree Classifier for interpretable, rule-based decisions\n\n✔ Clean and minimal Streamlit interface for live prediction\n\n✔ Exported model and vectorizer using pickle for efficient deployment\n\n✔ Well-organized code structure for easy understanding and modification\n\n# 🛠️ Libraries Used\n\nPandas\n\nNLTK for NLP and text processing\n\nScikit-learn for model training and evaluation\n\nStreamlit for app deployment\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanastasius21%2Ffakenewsmodel","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanastasius21%2Ffakenewsmodel","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanastasius21%2Ffakenewsmodel/lists"}