{"id":24388905,"url":"https://github.com/huacenxu/covid-morality","last_synced_at":"2026-04-30T05:34:12.140Z","repository":{"id":198931004,"uuid":"423955256","full_name":"huacenxu/COVID-Morality","owner":"huacenxu","description":"This project builds a novel liberty dictionary to quantify liberty morality—a concept missing from the extended Moral Foundations Dictionary (eMFD)—and leverages it to study the relationship between audience engagement and COVID-related news.","archived":false,"fork":false,"pushed_at":"2022-12-28T21:05:02.000Z","size":8982,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-28T22:58:33.217Z","etag":null,"topics":["academic-project","ai","coronavirus","covid-19","embedding-models","nlp","nlp-machine-learning"],"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/huacenxu.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}},"created_at":"2021-11-02T18:25:12.000Z","updated_at":"2024-12-29T15:22:00.000Z","dependencies_parsed_at":null,"dependency_job_id":"6650e4f5-fd46-45fe-97f5-5b63e5112510","html_url":"https://github.com/huacenxu/COVID-Morality","commit_stats":null,"previous_names":["huacenxu/covid-morality"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/huacenxu/COVID-Morality","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/huacenxu%2FCOVID-Morality","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/huacenxu%2FCOVID-Morality/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/huacenxu%2FCOVID-Morality/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/huacenxu%2FCOVID-Morality/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/huacenxu","download_url":"https://codeload.github.com/huacenxu/COVID-Morality/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/huacenxu%2FCOVID-Morality/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32456165,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-29T22:27:22.272Z","status":"online","status_checked_at":"2026-04-30T02:00:05.929Z","response_time":57,"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":["academic-project","ai","coronavirus","covid-19","embedding-models","nlp","nlp-machine-learning"],"created_at":"2025-01-19T14:58:03.859Z","updated_at":"2026-04-30T05:34:12.122Z","avatar_url":"https://github.com/huacenxu.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## COVID MORALITY\n\n### Introduction\n\nThis repository includes code and trained models corresponding to our research on covid morality (please run the notebooks in sequence). Our research explores the relationship between morality and audience engagement on Covid-19 related issues. We generated a liberty dictionary and then generate post level liberty score. This allows us to quantify liberty morality, which is missing in the extended moral foundation dictionary (eMFDs). \n\n\u003ca href=\"https://docs.google.com/presentation/d/1P02BEcFpWBeF6pBoh8xLRv3I8Cl3dhCI/edit?usp=sharing\u0026ouid=111383536844814990723\u0026rtpof=true\u0026sd=true\"\u003eAn ealier version of this research\u003c/a\u003e has been prestend at the ICA conference at Pairs, France (Virtual). When using this repository, please considering give it a star (top right corner) and citing below: \n\nYilang Peng \u0026 Huacen Xu(2022). \"Pandemic Politics, Moralized: How Morality Predicts Audience Engagement with COVID-19 Messages from Partisan and Science Media on Facebook\". Presented at 72nd Annual ICA Conference, Paris, France (virtual). \n\n### Data\nWe extracted textual data from Facebook public pages, then transformed and loaded them into a python notebook. The data is \u003ca href=\"https://drive.google.com/drive/folders/1arjfRysDY4nwcsgwTbKBCkYeLl7tq3SB?usp=sharing\"\u003ehere.\u003c/a\u003e \n\n### Install\nWe used the Anaconda navigator to run the python notebook (version: 6.4.8). No other software is needed to run the code.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhuacenxu%2Fcovid-morality","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhuacenxu%2Fcovid-morality","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhuacenxu%2Fcovid-morality/lists"}