{"id":22774274,"url":"https://github.com/krik8235/ml-project-sentiment-analysis","last_synced_at":"2026-04-11T13:03:57.241Z","repository":{"id":267305828,"uuid":"900836215","full_name":"krik8235/ml-project-sentiment-analysis","owner":"krik8235","description":"Build a machine learning model for sentimental analysis using NLTK.","archived":false,"fork":false,"pushed_at":"2024-12-09T15:18:16.000Z","size":152,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-30T13:11:31.190Z","etag":null,"topics":["kaggle","kaggle-dataset","machine-learning","machine-learning-algorithms","nltk","nltk-library","numpy","pandas","python3","seaborn","sklearn"],"latest_commit_sha":null,"homepage":"https://medium.com/@kuriko-iwai/88bb17583358","language":"Python","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/krik8235.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}},"created_at":"2024-12-09T15:01:25.000Z","updated_at":"2024-12-09T15:19:19.000Z","dependencies_parsed_at":"2024-12-09T16:25:41.468Z","dependency_job_id":"5074c0ad-1a1e-4fef-8022-d4a530429340","html_url":"https://github.com/krik8235/ml-project-sentiment-analysis","commit_stats":null,"previous_names":["krik8235/ml-project-sentiment-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/krik8235/ml-project-sentiment-analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krik8235%2Fml-project-sentiment-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krik8235%2Fml-project-sentiment-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krik8235%2Fml-project-sentiment-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krik8235%2Fml-project-sentiment-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/krik8235","download_url":"https://codeload.github.com/krik8235/ml-project-sentiment-analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/krik8235%2Fml-project-sentiment-analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31681212,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-11T08:18:19.405Z","status":"ssl_error","status_checked_at":"2026-04-11T08:17:08.892Z","response_time":54,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["kaggle","kaggle-dataset","machine-learning","machine-learning-algorithms","nltk","nltk-library","numpy","pandas","python3","seaborn","sklearn"],"created_at":"2024-12-11T18:13:32.251Z","updated_at":"2026-04-11T13:03:57.204Z","avatar_url":"https://github.com/krik8235.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Overview\n\nBuild a machine learning model for sentimental analysis using Twitter data.\n\n\n- [Medium story](https://medium.com/@kuriko-iwai/88bb17583358?source=friends_link\u0026sk=122d74d93dbacd7906330184b1254b80)\n\n- Dataframe\n\n\u003cp align=\"center\"\u003e\n    \u003cimg src=\"/images/terminal.png\" width=\"500\"\u003e\n\u003c/p\u003e\n\n\n## Usage\n1. Download [sample dataset](https://www.kaggle.com/datasets/kazanova/sentiment140?resource=download) using [kagglehub](https://github.com/Kaggle/kagglehub)\n\n2. Pre-process the text data:\n    - **Lowercasing**: Convert all text to lowercase for consistency.\n    - **Stop word removal**: Eliminate common words like \"the,\" \"a,\" and \"is\" that don't contribute to sentiment analysis.\n    - **Punctuation mark removal**: Remove punctuation marks like commas, periods, and exclamation points.\n    - **Stemming**: Reducing the word to its base form of the derived stem\n    - **Lemmatizing**: Reducing the word to its root form (lemma)\n\n\n3. Build and train a model using `Bernoulli Naive Bayes Classifier`.\n\n4. Visualize the result.\n\n5. Evaluate the performance using `accuracy score`, `confusion matrix`, and `ROC-AUC curve`.\n\n\n## Setup\n1. Install dependencies\n    ```\n    pip shell\n    pip install -r requirements.txt\n    ```\n\n2. Run the app\n    ```\n    pipenv shell\n    python main.py\n    ```\n\n\n## Results\n\u003cp align=\"center\"\u003e\n    \u003cimg src=\"images/confusion_matrix.png\" width=\"45%\"\u003e\n     \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\n    \u003cimg src=\"images/roc_curve.png\" width=\"45%\"\u003e\n\u003c/p\u003e","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkrik8235%2Fml-project-sentiment-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkrik8235%2Fml-project-sentiment-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkrik8235%2Fml-project-sentiment-analysis/lists"}