What impact does the number of followers have on TikTok view counts?


In a previous post, we estimated the impact of various metrics on the view counts for a video. This post extends that analysis to include information about the creator’s metrics, notably their follower count. Key results:
  1. Each additional follower increases the expected view count by 0.1 (i.e. ~10% of followers see each video)
  2. Other results are qualitatively similar (i.e. you need ~0.2 likes per view in order to have your video be promoted; share and comment counts are not predictive)

Detailed results

Please refer to our previous post for more information on the data set and methods used.


Transformation
Regression Type
Shares
Comments
Likes
Follower Count
Intercept
Alpha
R^2
Normal
Lasso
0.00
0.00
5.03
0.10
-1176.69
100000000.00
0.89
Normal
Ridge
-3.73
-10.95
5.17
0.10
-2334.26
100000000.00
0.89
Normal
OLS
-3.74
-10.98
5.17
0.10
-2337.18
N/A
0.89
Log
Lasso
0.00
-0.06
0.96
0.10
1.36
0.01
0.96
Log
Ridge
0.01
-0.09
0.97
0.10
1.34
1.00
0.96
Log
OLS
0.01
-0.09
0.97
0.10
1.34
N/A
0.96
None
Lasso
0.00
0.00
4.56
0.00
10416.20
37200000.00
0.80
None
Ridge
25.17
-0.26
4.41
0.00
9774.50
100000000.00
0.81
None
OLS
27.05
-0.26
4.40
0.00
9752.73
N/A
0.84
Logarithm
Lasso
-0.03
-0.05
1.08
0.00
1.64
0.01
0.95
Logarithm
Ridge
-0.04
-0.08
1.10
0.00
1.61
1.00
0.95
Logarithm
OLS
-0.04
-0.08
1.10
0.00
1.61
N/A
0.95


Normal

As before, these graphs plot the actual number of views a video received vs. the number predicted by the regression.

Log-transformed


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