{"id":28719743,"url":"https://github.com/khip01/sentiment-analysis","last_synced_at":"2026-07-21T18:38:45.376Z","repository":{"id":271332051,"uuid":"913084077","full_name":"Khip01/sentiment-analysis","owner":"Khip01","description":"sentiment analysis of the Indonesian language","archived":false,"fork":false,"pushed_at":"2025-01-07T04:06:14.000Z","size":48,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-07-21T18:38:28.553Z","etag":null,"topics":["basic","naive-bayes-classifier","python","rule-based-nlp","self-teaching","sentiment-analysis"],"latest_commit_sha":null,"homepage":"","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/Khip01.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,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-01-07T02:10:27.000Z","updated_at":"2025-03-12T08:43:49.000Z","dependencies_parsed_at":null,"dependency_job_id":"c5c375b0-3ae4-4bbd-a741-08bd97b922c9","html_url":"https://github.com/Khip01/sentiment-analysis","commit_stats":null,"previous_names":["khip01/sentiment-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Khip01/sentiment-analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Khip01%2Fsentiment-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Khip01%2Fsentiment-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Khip01%2Fsentiment-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Khip01%2Fsentiment-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Khip01","download_url":"https://codeload.github.com/Khip01/sentiment-analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Khip01%2Fsentiment-analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35734232,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-07-20T02:08:10.276Z","status":"online","status_checked_at":"2026-07-21T02:00:06.728Z","response_time":109,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["basic","naive-bayes-classifier","python","rule-based-nlp","self-teaching","sentiment-analysis"],"created_at":"2025-06-15T06:04:34.771Z","updated_at":"2026-07-21T18:38:45.367Z","avatar_url":"https://github.com/Khip01.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sentiment Analysis \nContains 2 simple projects which have the same goal, which is to analyze sentiment, whether the sentiment is positive, negative or neutral. **The sentiment analyzed is Indonesian sentiment.** \n\n## Rule Based\nRule-based sentiment analysis here is a sentiment analysis method using predefined logic rules. The rules are determined according to the **list of keywords** that have been given in the `words.txt` file whether they are negative or positive words **without using data training**. \n\n## Naive Bayes\nSentiment analysis Naive Bayes here is a technique for analyzing sentiment using the Naive Bayes machine learning method. This method **uses data training to learn the probability of each word appearing in a positive, negative or neutral**. \nWhich later from the results of the Naive Bayes model will **produce a probability that can later identify a word** including positive or negative or neutral words.\n\n# Instruction \nTo run either of the projects, we have the same steps:\n- go to one of the naive_bayes or rule_based projects with `cd \"folder_project_name\"`\n- create a virtual environment from python first using `python -m venv .venv`\n- activate the virtual environment according to your Operating System\n- install all the requirement libraries needed by running `pip install requirements.txt`\n- run the main.py file with `python -m main`\n\n\n### Note:\nAlthough this program lacks accuracy in solving problems, it was created for my own personal learning and as an experiment in machine learning. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkhip01%2Fsentiment-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkhip01%2Fsentiment-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkhip01%2Fsentiment-analysis/lists"}