{"id":25029063,"url":"https://github.com/danzek/email-formality-detection","last_synced_at":"2025-04-13T16:09:51.599Z","repository":{"id":23199613,"uuid":"26556226","full_name":"danzek/email-formality-detection","owner":"danzek","description":"Determine whether an email is formally or informally written","archived":false,"fork":false,"pushed_at":"2018-01-19T21:41:18.000Z","size":6476,"stargazers_count":3,"open_issues_count":0,"forks_count":2,"subscribers_count":3,"default_branch":"mysql","last_synced_at":"2025-04-13T16:09:47.746Z","etag":null,"topics":[],"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/danzek.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":"2014-11-12T21:07:41.000Z","updated_at":"2023-02-25T23:43:51.000Z","dependencies_parsed_at":"2022-08-21T21:31:32.971Z","dependency_job_id":null,"html_url":"https://github.com/danzek/email-formality-detection","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danzek%2Femail-formality-detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danzek%2Femail-formality-detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danzek%2Femail-formality-detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/danzek%2Femail-formality-detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/danzek","download_url":"https://codeload.github.com/danzek/email-formality-detection/tar.gz/refs/heads/mysql","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248741204,"owners_count":21154255,"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":[],"created_at":"2025-02-05T20:57:52.773Z","updated_at":"2025-04-13T16:09:51.571Z","avatar_url":"https://github.com/danzek.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# email-formality-detection [![No Maintenance Intended](http://unmaintained.tech/badge.svg)](http://unmaintained.tech/)\n\nPredict whether an email is formally or informally written. `data/prep_corpus.py` writes the emails to a SQLite\ndatabase. `process_corpus.py` creates a text file with extracted features in LibSVM format (for supervised machine\nlearning). `data/classifier_app` is a web application for framework validation and simplifying manual classification \nof each email as either formal or informal.\n\nThis project uses the Enron email corpus, retrieved \nfrom [https://www.cs.cmu.edu/~./enron/](https://www.cs.cmu.edu/~./enron/). This is a group project for CNIT499NLT \nNatural Language Technologies at Purdue University. The course instructor is Dr. Julia Taylor. \n\n## Group Members\n\n - Dan O'Day\n - Robert Hinh\n - Upasita Jain\n - Sangmi Shin\n - Penghao Wang\n\n## License\n\n[MIT](https://github.com/danzek/email-formality-detection/blob/master/LICENSE)\n\n## Database\n\nThe `mysql` branch is the main branch with all of the features and up-to-date code. However, the `master` branch uses sqlite rather than MySQL, and is thus easier to run and develop locally. Initial development took place with sqlite, but eventually moved to MySQL since that is the most efficient supported database type on PythonAnywhere hosting service.\n\n## How to Test A Single Feature\n\nBegin inside the directory where you've extracted this project. Using an interactive Python shell (symbolized by `\u003e\u003e\u003e` below\u0026mdash;**do not retype the prompt symbols**), do the following:\n\n    \u003e\u003e\u003e from data.models import Corpus\n    \nNext import your feature(s):\n\n    \u003e\u003e\u003e from features.myfeaturefile import myfeature\n\nNow instantiate the corpus and select a specific email by its ID number:\n\n    \u003e\u003e\u003e c = Corpus()\n    \u003e\u003e\u003e email_generator_object = c.fetch_all_emails(column=\"id\", query=\"120000\", exact_match=True)\n    \u003e\u003e\u003e email = next(email_generator_object)\n\nNow you have the email object with the specified id. You can pass it to your previously imported feature by using the feature function name:\n\n    \u003e\u003e\u003e myfeature(email)\n\nThe feature should return the specified metric.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanzek%2Femail-formality-detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdanzek%2Femail-formality-detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdanzek%2Femail-formality-detection/lists"}