{"id":25866110,"url":"https://github.com/guiarpi/lgbtqi-hate-crime-analysis","last_synced_at":"2026-06-09T11:31:26.926Z","repository":{"id":279493538,"uuid":"938995698","full_name":"guiarpi/LGBTQI-Hate-Crime-Analysis","owner":"guiarpi","description":"Machine Learning analysis of LGBTQI+ hate crimes in the U.S","archived":false,"fork":false,"pushed_at":"2025-02-25T20:43:48.000Z","size":2,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-25T21:33:32.858Z","etag":null,"topics":["decision-trees","eda","etl","k-means-clustering","knn-classification","linear-regression","machine-learning","multiple-linear-regression","r","random-forest","rstudio","sql","tableau"],"latest_commit_sha":null,"homepage":"","language":null,"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/guiarpi.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":"2025-02-25T20:31:23.000Z","updated_at":"2025-02-25T20:55:17.000Z","dependencies_parsed_at":"2025-02-25T21:43:37.701Z","dependency_job_id":null,"html_url":"https://github.com/guiarpi/LGBTQI-Hate-Crime-Analysis","commit_stats":null,"previous_names":["guiarpi/predicting-lgbtqi-hate-crimes-in-the-u.s.-using-machine-learning"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guiarpi%2FLGBTQI-Hate-Crime-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guiarpi%2FLGBTQI-Hate-Crime-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guiarpi%2FLGBTQI-Hate-Crime-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/guiarpi%2FLGBTQI-Hate-Crime-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/guiarpi","download_url":"https://codeload.github.com/guiarpi/LGBTQI-Hate-Crime-Analysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241448167,"owners_count":19964423,"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":["decision-trees","eda","etl","k-means-clustering","knn-classification","linear-regression","machine-learning","multiple-linear-regression","r","random-forest","rstudio","sql","tableau"],"created_at":"2025-03-02T02:21:49.690Z","updated_at":"2026-06-09T11:31:26.921Z","avatar_url":"https://github.com/guiarpi.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Predicting-LGBTQI-Hate-Crimes-in-the-U.S.-Using-Machine-Learning\n\n\n## Project Overview: \n~Brief description of the project, its goals, and key findings~\n\nIn this project, I examined hate crimes against LGBTQI+ individuals in the U.S. from 1991 to 2019, focusing on factors like income inequality, victim counts, LGBTQI+ population size, and anti-LGBTQI+ laws. **Machine learning algorithms** were used to predict and classify these crimes, with an emphasis on evaluating their accuracy. I used different data tools during the elaboration of this study, including **SQL** (for ETL), **R** (EDA and ML) and **Tableau** (Visualizations and Interactive Dashboard).\n\n**Key Strengths**\n\n- **Relevance of Topic:** The project addresses a socially significant issue.\n\n- **Use of ML Algorithms:** I have applied a variety of ML techniques (Decision Tree, Random Forest, K-Means, K-NN) to analyze the dataset.\n\n- **Data Enrichment:** I have added external data (e.g., LGBTQI+ population, Gini Index, hate crime laws) to enhance the analysis.\n\n- **Visualizations:** The use of Tableau and Excel for visualizations adds a layer of clarity to the findings.\n\n- **CRISP-DM Methodology:** The structured approach to data mining is a strong point.\n\n\n\n\n## Dataset: \nInformation about the dataset (source, variables, etc.).\n\n## Methodology: \nSummary of the techniques used (e.g., CRISP-DM, ML algorithms).\n\n## Results: \nKey insights and visualizations.\n\n## How to Run the Code: \nStep-by-step instructions for reproducing the analysis.\n\n## Dependencies: \nList of libraries and tools used (e.g., RStudio, Tableau).\n\n## Future Work: \n\n- Integrating social media data for real-time hate crime prediction.\n\n- Exploring other ML techniques (e.g., neural networks, ensemble methods).\n\n- Expanding the analysis to other countries or regions.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fguiarpi%2Flgbtqi-hate-crime-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fguiarpi%2Flgbtqi-hate-crime-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fguiarpi%2Flgbtqi-hate-crime-analysis/lists"}