{"id":24763235,"url":"https://github.com/beyondmayowo/sentiment-analysis","last_synced_at":"2025-06-17T12:33:54.080Z","repository":{"id":272419883,"uuid":"915637888","full_name":"beyondmayOwO/sentiment-analysis","owner":"beyondmayOwO","description":"Sentiment analysis using IBM Watson NLU API","archived":false,"fork":false,"pushed_at":"2025-01-19T09:43:27.000Z","size":2321,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-23T14:34:43.220Z","etag":null,"topics":["flask-application","sentiment-analysis","watson-nlu-api","webapp"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/beyondmayOwO.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":"2025-01-12T12:09:29.000Z","updated_at":"2025-01-19T09:45:46.000Z","dependencies_parsed_at":null,"dependency_job_id":"4432a674-50d7-4c17-9b44-9f81175eb3a7","html_url":"https://github.com/beyondmayOwO/sentiment-analysis","commit_stats":null,"previous_names":["beyondmayowo/sentiment-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/beyondmayOwO/sentiment-analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beyondmayOwO%2Fsentiment-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beyondmayOwO%2Fsentiment-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beyondmayOwO%2Fsentiment-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beyondmayOwO%2Fsentiment-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/beyondmayOwO","download_url":"https://codeload.github.com/beyondmayOwO/sentiment-analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/beyondmayOwO%2Fsentiment-analysis/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260358317,"owners_count":22997009,"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":["flask-application","sentiment-analysis","watson-nlu-api","webapp"],"created_at":"2025-01-28T20:26:27.676Z","updated_at":"2025-06-17T12:33:49.066Z","avatar_url":"https://github.com/beyondmayOwO.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# sentiment-analysis\n\nSentiment analysis using IBM Watson NLU API. It can detect the sentiment of the text and the score. Web application deployed on the Flask server.\n\n## Demo\n\n![](demo.gif)\n\n- User can input the sentence and it will detect three sentiment of the text: positive, negative, and neutral\n- It will also put the score of the text\n- If the input is nonesense, it will displays 'Invalid text'\n- If there is no input, it will displays 'Empty input'\n\n## What I Learned\n- Created an AI based sentiment analysis application using Watson NLU API.\n- Formatted the output received from the Watson NLU API to extract relevant information from it.\n- Packaged the application and made it importable to any python code for usage.\n- Ran unit tests on the application and checked the validity of its outputs for different inputs.\n- Deployed the application using Flask framework.\n- Incorporated error handling capability in the application, such that a response code of 500 receives an appropriate response from the application.\n- Ran static code analysis on the code files to confirm their adherence to the PEP8 guidelines.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbeyondmayowo%2Fsentiment-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbeyondmayowo%2Fsentiment-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbeyondmayowo%2Fsentiment-analysis/lists"}