{"id":13528079,"url":"https://github.com/rasbt/musicmood","last_synced_at":"2026-01-25T08:31:07.239Z","repository":{"id":24286686,"uuid":"27681574","full_name":"rasbt/musicmood","owner":"rasbt","description":"A machine learning approach to classify songs by mood.","archived":false,"fork":false,"pushed_at":"2016-11-02T00:23:40.000Z","size":55916,"stargazers_count":419,"open_issues_count":5,"forks_count":107,"subscribers_count":31,"default_branch":"master","last_synced_at":"2025-03-29T17:26:45.724Z","etag":null,"topics":["exploratory-data-analysis","lyrics","machine-learning","mood","song-dataset"],"latest_commit_sha":null,"homepage":null,"language":"OpenEdge ABL","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rasbt.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2014-12-07T19:20:40.000Z","updated_at":"2025-03-01T05:57:51.000Z","dependencies_parsed_at":"2022-08-27T02:05:10.626Z","dependency_job_id":null,"html_url":"https://github.com/rasbt/musicmood","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/rasbt/musicmood","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rasbt%2Fmusicmood","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rasbt%2Fmusicmood/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rasbt%2Fmusicmood/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rasbt%2Fmusicmood/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rasbt","download_url":"https://codeload.github.com/rasbt/musicmood/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rasbt%2Fmusicmood/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28749285,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-25T07:58:02.558Z","status":"ssl_error","status_checked_at":"2026-01-25T07:57:57.153Z","response_time":113,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: 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":["exploratory-data-analysis","lyrics","machine-learning","mood","song-dataset"],"created_at":"2024-08-01T06:02:12.076Z","updated_at":"2026-01-25T08:31:07.012Z","avatar_url":"https://github.com/rasbt.png","language":"OpenEdge ABL","funding_links":[],"categories":["OpenEdge ABL"],"sub_categories":[],"readme":"# MusicMood\n\n### A machine learning approach to classify music by mood based on song lyrics.\n\nThis project is about building a music recommendation system for users who want to listen to *happy* songs. Such a system can not only be used to brighten up one's mood on a rainy weekend; especially in hospitals, other medical clinics, or public locations such as restaurants, the MusicMood classifier could be used to spread positive mood among people.\n\n\u003cbr\u003e\n\n### Links\n\n- [The web application](http://rasbt.pythonanywhere.com)\n- [The data collection IPython notebook](code/collect_data/data_collection.ipynb)\n- [The initial model training IPython notebook](code/classify_lyrics/nb_init_model.ipynb)\n- [The updated model training with white lists IPython notebook](code/classify_lyrics/nb_whitelist_model.ipynb)\n- [Experiments with Random Forests IPython notebook](code/classify_lyrics/random_forests.ipynb)\n- [An article about my experiences with this project](http://sebastianraschka.com/blog/2014/musicmood.html)\n- [A keynote presentation about this project](https://speakerdeck.com/rasbt/musicmood-machine-learning-in-automatic-music-mood-prediction-based-on-song-lyrics)\n- [A more technical report on arXiv](https://arxiv.org/abs/1611.00138)\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n### Sections\n\u003chr\u003e\n\n- [Dataset Summary](#dataset-summary)\n- [Exploratory Data Analysis](#exploratory-data-analysis)\n- [Results](#results)\n\n\u003chr\u003e\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n![](./images/flowchart.png)\n\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n\n## Dataset Summary\n[back to top](#sections)\n\n- A 10,000-song subset was downloaded from the [Million Song Dataset](http://labrosa.ee.columbia.edu/millionsong/pages/getting-dataset).\n- Lyrics were automatically downloaded from [LyricWikia](http://lyrics.wikia.com/Lyrics_Wiki) and all songs for which lyrics have not been available were removed from the dataset.\n - An English language filter was applied to detect and remove all non-English songs.\n -  The remaining songs were randomly subsampled into a 1000-song training dataset and 200-song validation dataset.\n\n\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n## Exploratory Data Analysis\n\n[back to top](#sections)\n\n![](./images/exploratory_1.png)\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n![](./images/wordclouds.png)\n\n\n\u003cbr\u003e\n\u003cbr\u003e\n\n\n## Results\n[back to top](#sections)\n\n\n![](./images/roc_best.png)\n\n![](./images/performance_table.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frasbt%2Fmusicmood","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frasbt%2Fmusicmood","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frasbt%2Fmusicmood/lists"}