                              OLS Regression Results                             
=================================================================================
Dep. Variable:     number O(n+1)-replies   R-squared:                       0.199
Model:                               OLS   Adj. R-squared:                  0.199
Method:                    Least Squares   F-statistic:                 5.941e+05
Date:                   Mon, 22 Jul 2024   Prob (F-statistic):               0.00
Time:                           09:31:47   Log-Likelihood:            -8.2498e+06
No. Observations:                4786218   AIC:                         1.650e+07
Df Residuals:                    4786215   BIC:                         1.650e+07
Df Model:                              2                                         
Covariance Type:               nonrobust                                         
==============================================================================
                 coef    std err          t      P>|t|      [0.025      0.975]
------------------------------------------------------------------------------
const          1.1760      0.001   1897.046      0.000       1.175       1.177
valence       -0.3745      0.001   -601.728      0.000      -0.376      -0.373
totalvotes     0.5306      0.001    852.573      0.000       0.529       0.532
==============================================================================
Omnibus:                  2293481.647   Durbin-Watson:                   1.752
Prob(Omnibus):                  0.000   Jarque-Bera (JB):         63398255.054
Skew:                           1.739   Prob(JB):                         0.00
Kurtosis:                      20.487   Cond. No.                         1.09
==============================================================================

Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.