{"id":19200388,"url":"https://github.com/glebpro/nlptermproject2017","last_synced_at":"2026-06-19T17:33:20.151Z","repository":{"id":77993078,"uuid":"107909786","full_name":"glebpro/nlptermproject2017","owner":"glebpro","description":"Automatic Classification of Persuasive Arguments, RIT, 2017","archived":false,"fork":false,"pushed_at":"2018-01-30T15:37:24.000Z","size":49148,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-02-23T05:26:44.227Z","etag":null,"topics":["arguments","nlp","persuasive","reddit"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/glebpro.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-10-22T23:06:50.000Z","updated_at":"2023-04-19T11:32:22.000Z","dependencies_parsed_at":"2023-03-03T04:45:22.074Z","dependency_job_id":null,"html_url":"https://github.com/glebpro/nlptermproject2017","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/glebpro/nlptermproject2017","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/glebpro%2Fnlptermproject2017","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/glebpro%2Fnlptermproject2017/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/glebpro%2Fnlptermproject2017/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/glebpro%2Fnlptermproject2017/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/glebpro","download_url":"https://codeload.github.com/glebpro/nlptermproject2017/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/glebpro%2Fnlptermproject2017/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34541970,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-19T02:00:06.005Z","response_time":61,"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":["arguments","nlp","persuasive","reddit"],"created_at":"2024-11-09T12:32:26.826Z","updated_at":"2026-06-19T17:33:20.130Z","avatar_url":"https://github.com/glebpro.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Automatic Classification of Persuasive Arguments\nTerm project for ENGL 681 _Introduction to Natural Language Processing_ at RIT, 2017.\n\n[@jdberlinski](https://github.com/jdberlinski)\n[@glebpro](https://github.com/glebpro)\n\n## Abstract:\nPublic web forums allow for massive online debate, especially on the community platform Reddit. The language of persuasive arguments can be found on the sub-community [/r/ChangeMyView](https://reddit.com/ChangeMyView), which encourages sharing views and discourse in a moderated public forum. To determine if there are any similarities between persuasive comments that were successful in changing a user's view we organized and labeled sets of argument examples, and found valuable features for classifying novel arguments through language modeling. Our model results saw 6% improved accuracy over the baseline, concluding that there are identifiable stylistic and topic features in effective arguments.\n\n[[Slides](slides.pdf)][[Paper](paper.pdf)]\n\n## Technicals\n\n#### Downloads\nTo download code: `$ git clone https://github.com/glebpro/nlptermproject2017`\n\nTo download corpus: [download link](https://drive.google.com/drive/folders/1Ki65wjOoVgLENWK1xgRMPaxdBrx5v8n9?usp=sharing). Data format explained [here](/corpus_utils/data_format.txt).\n\n#### Scripts\n\nTo generate your own corpus, gathering posts backwards in time from now:\n1. Populate [`corpus_utils/reddit.auth.json`](corpus_utils/reddit.auth.json) with your reddit credentials\n2. Run `$ python corpus_utils/download.py num_posts_to_collect`\n\nTo generate comment pairs, use:\n1. `$ python corpus_utils/comment_pairs.py CMV_##.jsonlist`\n\nFor the classifier:\n1. To extract features: `$ python model_files/get_features.py comment_pairs.jsonlist`\n2. To train new model: `$ python model_files/model.py`\n  - steps 1 and 2 might take hours\n3. To explore results: `$ python model_files/explore.py`\n  - to print results from included model\n\nAdditional utility scrips included for parsing [posts](corpus_utils/parse_jsonlist.py) and [comments](corpus_utils/parse_comments.py)\n\n#### Requirements\n[python](https://www.python.org/) \u003e= 3.4, [praw](https://praw.readthedocs.io/en/latest/index.html) \u003e= 5.2, [spacy](https://spacy.io/) \u003e= 2.0.3, [sklearn](http://scikit-learn.org/stable/) \u003e= 0.18.1, [numpy](http://www.numpy.org/) \u003e= 1.13.3, [nltk](http://www.nltk.org/) \u003e= 3.2.5\n\n#### License\nMIT licensed. See the bundled [LICENSE](/LICENSE) file for more details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fglebpro%2Fnlptermproject2017","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fglebpro%2Fnlptermproject2017","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fglebpro%2Fnlptermproject2017/lists"}