Title:

How Subscriber Count Impacts Interactions on YouTube

Our project investigates the impact of subscriber count on the average like-to-view ratio and average comment-to-view ratio for YouTube channels. Using the YouTube Data API, our project randomly selected over 300 channels and calculated the ratios for their top ten most viewed videos, while also picking up their total subscriber count. The data was then analyzed using scatter plots created in Google Sheets. The results suggest that there is no correlation between a channel's subscriber count and its average like-to-view and comment-to-view ratios. This study contributes to the understanding of the metrics that measure success on YouTube and informs content creators that whether videos will perform well is independent of the size of the channel.

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