twitter-image-analytics | project aims to analyze the GoPro 's Twitter uploads
kandi X-RAY | twitter-image-analytics Summary
kandi X-RAY | twitter-image-analytics Summary
twitter-image-analytics is a Python library. twitter-image-analytics has no bugs, it has no vulnerabilities and it has low support. However twitter-image-analytics build file is not available. You can download it from GitHub.
This project aims to analyze the GoPro's Twitter uploads, as they have a large variety of photos with different levels of engagement. Go Pro is a leading action camera manufacturer which also develops its own mobile apps and video-editing software. Firstly, we scraped Go Pro's twitter account for all the posts with images including the caption, number of likes, number of comments, and the URL of the image. Next, the images were passed through Google's Cloud Vision AI API to retrieve annotatation for each image. Using the image descriptors, topic modeling was applied to classify the posts in 5-6 themes. Finally, posts for each theme were analyzed for their performance using the engagement metrics. The analysis is particularly extremely useful for the brand as it highlights which specific photo themes create more engagement amongst their audience.
This project aims to analyze the GoPro's Twitter uploads, as they have a large variety of photos with different levels of engagement. Go Pro is a leading action camera manufacturer which also develops its own mobile apps and video-editing software. Firstly, we scraped Go Pro's twitter account for all the posts with images including the caption, number of likes, number of comments, and the URL of the image. Next, the images were passed through Google's Cloud Vision AI API to retrieve annotatation for each image. Using the image descriptors, topic modeling was applied to classify the posts in 5-6 themes. Finally, posts for each theme were analyzed for their performance using the engagement metrics. The analysis is particularly extremely useful for the brand as it highlights which specific photo themes create more engagement amongst their audience.
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Support
twitter-image-analytics has a low active ecosystem.
It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
twitter-image-analytics has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of twitter-image-analytics is current.
Quality
twitter-image-analytics has no bugs reported.
Security
twitter-image-analytics has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
twitter-image-analytics does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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twitter-image-analytics releases are not available. You will need to build from source code and install.
twitter-image-analytics has no build file. You will be need to create the build yourself to build the component from source.
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twitter-image-analytics Key Features
No Key Features are available at this moment for twitter-image-analytics.
twitter-image-analytics Examples and Code Snippets
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Community Discussions
No Community Discussions are available at this moment for twitter-image-analytics.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install twitter-image-analytics
You can download it from GitHub.
You can use twitter-image-analytics 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 twitter-image-analytics 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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