Depression_detection_using_Twitter_post | depression detection by using tweets
kandi X-RAY | Depression_detection_using_Twitter_post Summary
kandi X-RAY | Depression_detection_using_Twitter_post Summary
Depression_detection_using_Twitter_post is a Python library. Depression_detection_using_Twitter_post has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However Depression_detection_using_Twitter_post build file is not available. You can download it from GitHub.
this repo dedicated to the depression detection by using tweets of the users:. there are two kind of tweets that are required at this project: random tweets that do not indicate depression and tweets that shows the user may have the depression. the random tweets dataset could be download from the kaggle website by the following link:since there is no public dataset exists regardingthe depressive tweets, the essential dataset for this project taken by the websraper with the name of twint using the keyword depression by scraping all tweets in an one day span. the tweets which taken as the result of the scrapper may contain tweets that do not shows the user have the depression,such as tweets such as tweets linking to articles about depression. hence, the scrapped tweets need to be manually check for
this repo dedicated to the depression detection by using tweets of the users:. there are two kind of tweets that are required at this project: random tweets that do not indicate depression and tweets that shows the user may have the depression. the random tweets dataset could be download from the kaggle website by the following link:since there is no public dataset exists regardingthe depressive tweets, the essential dataset for this project taken by the websraper with the name of twint using the keyword depression by scraping all tweets in an one day span. the tweets which taken as the result of the scrapper may contain tweets that do not shows the user have the depression,such as tweets such as tweets linking to articles about depression. hence, the scrapped tweets need to be manually check for
Support
Quality
Security
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Support
Depression_detection_using_Twitter_post has a low active ecosystem.
It has 11 star(s) with 14 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
There are 0 open issues and 1 have been closed. On average issues are closed in 1 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Depression_detection_using_Twitter_post is current.
Quality
Depression_detection_using_Twitter_post has no bugs reported.
Security
Depression_detection_using_Twitter_post has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
Depression_detection_using_Twitter_post is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
Depression_detection_using_Twitter_post releases are not available. You will need to build from source code and install.
Depression_detection_using_Twitter_post has no build file. You will be need to create the build yourself to build the component from source.
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Depression_detection_using_Twitter_post Key Features
No Key Features are available at this moment for Depression_detection_using_Twitter_post.
Depression_detection_using_Twitter_post Examples and Code Snippets
No Code Snippets are available at this moment for Depression_detection_using_Twitter_post.
Community Discussions
No Community Discussions are available at this moment for Depression_detection_using_Twitter_post.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Depression_detection_using_Twitter_post
You can download it from GitHub.
You can use Depression_detection_using_Twitter_post like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use Depression_detection_using_Twitter_post like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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