| { | |
| "@context": "https://doi.org/10.5063/schema/codemeta-2.0", | |
| "@type": "SoftwareSourceCode", | |
| "name": "DEPRESSION-DETECTION-USING-TWEETS", | |
| "description": "An end-to-end machine learning solution designed to identify depressive characteristics in social media discourse using natural language processing and supervised learning techniques.", | |
| "identifier": "DEPRESSION-DETECTION-USING-TWEETS", | |
| "license": "https://spdx.org/licenses/MIT.html", | |
| "programmingLanguage": [ | |
| "Python", | |
| "NLP" | |
| ], | |
| "author": [ | |
| { | |
| "@type": "Person", | |
| "givenName": "Amey", | |
| "familyName": "Thakur", | |
| "id": "https://orcid.org/0000-0001-5644-1575" | |
| }, | |
| { | |
| "@type": "Person", | |
| "givenName": "Mega", | |
| "familyName": "Satish", | |
| "id": "https://orcid.org/0000-0002-1844-9557" | |
| } | |
| ], | |
| "dateReleased": "2022-06-05", | |
| "codeRepository": "https://github.com/Amey-Thakur/DEPRESSION-DETECTION-USING-TWEETS", | |
| "developmentStatus": "complete", | |
| "applicationCategory": "Machine Learning / Sentiment Analysis", | |
| "keywords": [ | |
| "Depression Detection", | |
| "Twitter", | |
| "Machine Learning", | |
| "NLP", | |
| "Social Media Analytics" | |
| ] | |
| } |