Hi,
I'm involved in a project where I'm analyzing public data from a popular cam site. I thought it might be interesting to share some insights from this data with you all. The data was collected every 5 minutes from August 1, 2023, to December 31, 2023, and specifically focuses on female models.
Hourly Audience
Here's a graph showing the average number of viewers for each hour of the day. The times are in UTC (Coordinated Universal Time),
New Models
During this period, there were 9,162 new models.
Of these, 4,041 stopped streaming on the platform. On average, these models streamed for about 17 days before stopping.
Median Number of Followers in the First 60 Days
Let's talk about the median, which is a simple concept. Imagine lining up all the new models according to their number of followers. The model in the middle of this line-up is our median. This means half of the models have more followers than this median model, and half have fewer.
It shows the importance of the 7 first days.
New models have been grouped into four categories based on their follower counts after 60 days, known as quartiles. Think of it like slicing a cake into four equal parts. Each slice (or quartile) has a range of follower counts. The first quartile has the models with the fewest followers, and the fourth quartile has those with the most.
The next graph shows how the number of followers grew over the first 60 days for each of these four groups.
Keywords Impacting Viewer Growth
Finally, I've prepared a file that lists the keywords in room subjects that influence the growth of viewers the most in the next 5 minutes, the correlation coef between the keyword and the viewers increase is indicated just after the keyword. Note that some of the language used might be explicit.
Top 100 keywords
Why am I sharing this? Because I believe these insights can be helpful to you, and also because I might need your assistance with my project soon. I'll share more details about that later!
I hope you find this data interesting and useful. If you want more stats from this period, just let me know, and I'll do my best to provide them.
I'm involved in a project where I'm analyzing public data from a popular cam site. I thought it might be interesting to share some insights from this data with you all. The data was collected every 5 minutes from August 1, 2023, to December 31, 2023, and specifically focuses on female models.
Hourly Audience
Here's a graph showing the average number of viewers for each hour of the day. The times are in UTC (Coordinated Universal Time),
New Models
During this period, there were 9,162 new models.
Of these, 4,041 stopped streaming on the platform. On average, these models streamed for about 17 days before stopping.
Median Number of Followers in the First 60 Days
Let's talk about the median, which is a simple concept. Imagine lining up all the new models according to their number of followers. The model in the middle of this line-up is our median. This means half of the models have more followers than this median model, and half have fewer.
It shows the importance of the 7 first days.
New models have been grouped into four categories based on their follower counts after 60 days, known as quartiles. Think of it like slicing a cake into four equal parts. Each slice (or quartile) has a range of follower counts. The first quartile has the models with the fewest followers, and the fourth quartile has those with the most.
The next graph shows how the number of followers grew over the first 60 days for each of these four groups.
Keywords Impacting Viewer Growth
Finally, I've prepared a file that lists the keywords in room subjects that influence the growth of viewers the most in the next 5 minutes, the correlation coef between the keyword and the viewers increase is indicated just after the keyword. Note that some of the language used might be explicit.
Top 100 keywords
Why am I sharing this? Because I believe these insights can be helpful to you, and also because I might need your assistance with my project soon. I'll share more details about that later!
I hope you find this data interesting and useful. If you want more stats from this period, just let me know, and I'll do my best to provide them.