Difference between revisions of "Group04 Interim"
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To help SGAG conduct a comprehensive competitor analysis on YouTube, we scraped all metal data from Night Owl Cinematic, TheSmartLocal and SGAG’s YouTube channels using YouTube-DL into .json files. Using Python, we parsed the necessary data into a csv format before importing the data into JMP Pro. | To help SGAG conduct a comprehensive competitor analysis on YouTube, we scraped all metal data from Night Owl Cinematic, TheSmartLocal and SGAG’s YouTube channels using YouTube-DL into .json files. Using Python, we parsed the necessary data into a csv format before importing the data into JMP Pro. | ||
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| + | Removing Outliers | ||
After which, we removed outliers based off view counts as view count is the only indicator of a viral YouTube video. It is also important to note that we removed such outliers by channel as each channel would have different levels of average performances. The table below shows examples of outliers: | After which, we removed outliers based off view counts as view count is the only indicator of a viral YouTube video. It is also important to note that we removed such outliers by channel as each channel would have different levels of average performances. The table below shows examples of outliers: | ||
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[[Image: outliers.png |600px|middle]] | [[Image: outliers.png |600px|middle]] | ||
| + | As mentioned in the proposal report, the Pokemon Go prank was a viral video as it was a prank carried out during the Pokemon Go craze by the SGAG team who tricked the public crowd into thinking there is a Snorlax nearby, when there was none. | ||
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Revision as of 13:27, 18 February 2018
| GROUP4 |
 HOMEPAGE
|
 PROJECT OVERVIEW
|
 PROJECT FINDINGS
|
 PROJECT MANAGEMENT
|
 DOCUMENTATION
|
 ANALY482 MAIN
|
| PROPOSAL | FINAL |
|---|
Exploratory Data Analysis
Objective 3: Competitor Analysis
YouTube Posts
To help SGAG conduct a comprehensive competitor analysis on YouTube, we scraped all metal data from Night Owl Cinematic, TheSmartLocal and SGAG’s YouTube channels using YouTube-DL into .json files. Using Python, we parsed the necessary data into a csv format before importing the data into JMP Pro.
Removing Outliers
After which, we removed outliers based off view counts as view count is the only indicator of a viral YouTube video. It is also important to note that we removed such outliers by channel as each channel would have different levels of average performances. The table below shows examples of outliers:
As mentioned in the proposal report, the Pokemon Go prank was a viral video as it was a prank carried out during the Pokemon Go craze by the SGAG team who tricked the public crowd into thinking there is a Snorlax nearby, when there was none.
Methodology
In progress.
