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public repository of the uncongeniality_analysis. Initial publication
2024-07-22 09:51:10 +02:00
# Analysis Results for July 22, 2024
Descriptive Analysis: Extended_Data_Table_1_Descriptive_Data_for_different_comment_levels
```
Data: data
Metrics: [Metric(operation='count', column=None), Metric(operation='count_nonzero', column='totalvotes'), Metric(operation='sum', column='totalvotes'), Metric(operation='mean', column='totalvotes'), Metric(operation='std_dev', column='totalvotes'), Metric(operation='sum', column='upvotes'), Metric(operation='sum', column='downvotes'), Metric(operation='mean', column='bayes-corrected (q=0.25) valence'), Metric(operation='std_dev', column='bayes-corrected (q=0.25) valence'), Metric(operation='mean', column='bayes-corrected (q=0.25) extremity'), Metric(operation='std_dev', column='bayes-corrected (q=0.25) extremity')]
Group By: order
```
| | total_count | totalvotes_nonzero | totalvotes_sum | totalvotes_mean | totalvotes_std_dev | upvotes_sum | downvotes_sum | bayes-corrected (q=0.25) valence_mean | bayes-corrected (q=0.25) valence_std_dev | bayes-corrected (q=0.25) extremity_mean | bayes-corrected (q=0.25) extremity_std_dev |
|:------|--------------:|---------------------:|-----------------:|------------------:|---------------------:|--------------:|----------------:|----------------------------------------:|-------------------------------------------:|------------------------------------------:|---------------------------------------------:|
| Total | 2.01613e+07 | 1.47066e+07 | 1.54821e+08 | 7.67914 | 11.5568 | 1.02022e+08 | 5.27992e+07 | 0.177047 | 0.202194 | 0.315847 | 0.110416 |
| 0 | 6.06997e+06 | 4.78622e+06 | 7.7965e+07 | 12.8444 | 15.8859 | 5.07299e+07 | 2.72351e+07 | 0.173957 | 0.224284 | 0.308131 | 0.119965 |
| 1 | 6.75509e+06 | 5.05012e+06 | 4.63205e+07 | 6.85713 | 9.43416 | 3.19706e+07 | 1.43499e+07 | 0.192882 | 0.192026 | 0.31989 | 0.108792 |
| 2 | 3.78656e+06 | 2.6083e+06 | 1.81262e+07 | 4.787 | 7.11937 | 1.14148e+07 | 6.71148e+06 | 0.164022 | 0.19273 | 0.317586 | 0.103832 |
| 3 | 3.5497e+06 | 2.26195e+06 | 1.24098e+07 | 3.496 | 5.50151 | 7.90706e+06 | 4.5027e+06 | 0.16325 | 0.182324 | 0.321141 | 0.0988151 |
Descriptive Analysis: Extended_Data_Table_2_Descriptive_Data_for_different_news_categories
```
Data: data
Metrics: [Metric(operation='count', column=None), Metric(operation='sum', column='number O(n+1)-replies'), Metric(operation='count_nonzero', column='number O(n+1)-replies'), Metric(operation='count_nonzero', column='totalvotes'), Metric(operation='sum', column='totalvotes'), Metric(operation='sum', column='upvotes'), Metric(operation='sum', column='downvotes'), Metric(operation='count_nonzero', column='totalvotes'), Metric(operation='mean', column='valence'), Metric(operation='std_dev', column='valence'), Metric(operation='mean', column='bayes-corrected (q=0.25) valence'), Metric(operation='std_dev', column='bayes-corrected (q=0.25) valence'), Metric(operation='mean', column='extremity'), Metric(operation='std_dev', column='extremity'), Metric(operation='mean', column='bayes-corrected (q=0.25) extremity'), Metric(operation='std_dev', column='bayes-corrected (q=0.25) extremity')]
Group By: section
```
| | total_count | number O(n+1)-replies_sum | number O(n+1)-replies_nonzero | totalvotes_nonzero | totalvotes_sum | upvotes_sum | downvotes_sum | valence_mean | valence_std_dev | bayes-corrected (q=0.25) valence_mean | bayes-corrected (q=0.25) valence_std_dev | extremity_mean | extremity_std_dev | bayes-corrected (q=0.25) extremity_mean | bayes-corrected (q=0.25) extremity_std_dev |
|:----------------|-----------------:|----------------------------:|--------------------------------:|---------------------:|-----------------:|-----------------:|-----------------:|---------------:|------------------:|----------------------------------------:|-------------------------------------------:|-----------------:|--------------------:|------------------------------------------:|---------------------------------------------:|
| Total | 2.01613e+07 | 1.40915e+07 | 7.49546e+06 | 1.47066e+07 | 1.54821e+08 | 1.02022e+08 | 5.27992e+07 | 0.180973 | 0.322102 | 0.177047 | 0.202194 | 0.326367 | 0.173164 | 0.315847 | 0.110416 |
| Backstage | 2638 | 1309 | 916 | 2091 | 19339 | 14013 | 5326 | 0.233963 | 0.306585 | 0.212235 | 0.186278 | 0.345784 | 0.170692 | 0.328434 | 0.109473 |
| Career | 125360 | 84283 | 47627 | 94139 | 991285 | 688567 | 302718 | 0.231447 | 0.317363 | 0.207642 | 0.203524 | 0.356256 | 0.165433 | 0.336509 | 0.106194 |
| Community | 2546 | 1519 | 921 | 1691 | 10943 | 7543 | 3400 | 0.229979 | 0.319679 | 0.200451 | 0.171317 | 0.352505 | 0.175451 | 0.327594 | 0.0984174 |
| Culture | 783764 | 492965 | 283683 | 594634 | 7.4852e+06 | 4.96592e+06 | 2.51928e+06 | 0.189242 | 0.314309 | 0.182377 | 0.207577 | 0.325727 | 0.168832 | 0.316507 | 0.11183 |
| Economy | 2.53271e+06 | 1.75303e+06 | 981305 | 1.83206e+06 | 1.54187e+07 | 1.04775e+07 | 4.94118e+06 | 0.196956 | 0.320061 | 0.187435 | 0.187799 | 0.331784 | 0.176493 | 0.318213 | 0.107722 |
| Family | 49628 | 31670 | 18194 | 38744 | 504399 | 350538 | 153861 | 0.220707 | 0.301459 | 0.204153 | 0.202007 | 0.333663 | 0.168096 | 0.322468 | 0.114288 |
| Fitness | 3010 | 2211 | 1182 | 2183 | 22484 | 14215 | 8269 | 0.159674 | 0.304319 | 0.162 | 0.186423 | 0.294188 | 0.17757 | 0.291518 | 0.114979 |
| Foreign affairs | 3.67727e+06 | 2.54442e+06 | 1.33077e+06 | 2.73427e+06 | 3.34839e+07 | 2.2654e+07 | 1.08299e+07 | 0.200258 | 0.325383 | 0.190467 | 0.21644 | 0.343568 | 0.167148 | 0.329924 | 0.110703 |
| Health | 232501 | 170195 | 87992 | 169188 | 1.8618e+06 | 1.22014e+06 | 641657 | 0.184245 | 0.324605 | 0.178142 | 0.207807 | 0.331904 | 0.170744 | 0.320003 | 0.109447 |
| History | 72480 | 47028 | 26802 | 56445 | 679183 | 472071 | 207112 | 0.220959 | 0.315349 | 0.203942 | 0.211781 | 0.347169 | 0.166553 | 0.333184 | 0.111218 |
| International | 1778 | 661 | 443 | 1021 | 5800 | 3874 | 1926 | 0.193512 | 0.378174 | 0.18493 | 0.19432 | 0.390006 | 0.168064 | 0.349551 | 0.0876688 |
| Internet | 498610 | 333659 | 186807 | 367308 | 3.6749e+06 | 2.46672e+06 | 1.20818e+06 | 0.209165 | 0.328664 | 0.193031 | 0.207946 | 0.351581 | 0.16781 | 0.333279 | 0.105377 |
| Miscellaneous | 1.96273e+06 | 1.35214e+06 | 729325 | 1.44919e+06 | 1.74751e+07 | 1.18991e+07 | 5.57597e+06 | 0.204879 | 0.322236 | 0.193042 | 0.211388 | 0.343485 | 0.166822 | 0.329243 | 0.109056 |
| Mobility | 554408 | 415352 | 219481 | 421827 | 3.50237e+06 | 2.19617e+06 | 1.3062e+06 | 0.160549 | 0.311911 | 0.161896 | 0.180023 | 0.301206 | 0.179831 | 0.295894 | 0.109983 |
| Politics | 5.11635e+06 | 3.45114e+06 | 1.90106e+06 | 3.67566e+06 | 3.91552e+07 | 2.56675e+07 | 1.34876e+07 | 0.174445 | 0.316334 | 0.173152 | 0.196045 | 0.316742 | 0.173701 | 0.308454 | 0.110588 |
| Psychology | 77714 | 49836 | 28755 | 59103 | 731898 | 505589 | 226309 | 0.206327 | 0.311541 | 0.194463 | 0.206588 | 0.33338 | 0.168776 | 0.322485 | 0.112718 |
| Relationships | 8131 | 4828 | 2914 | 6585 | 117075 | 86625 | 30450 | 0.24777 | 0.293584 | 0.227953 | 0.21253 | 0.348138 | 0.162397 | 0.336986 | 0.117751 |
| Science | 3.52556e+06 | 2.77414e+06 | 1.30784e+06 | 2.48028e+06 | 2.16604e+07 | 1.29048e+07 | 8.7556e+06 | 0.131249 | 0.325456 | 0.143581 | 0.192932 | 0.302174 | 0.178435 | 0.29727 | 0.109202 |
| Services | 15 | 6 | 4 | 13 | 70 | 49 | 21 | 0.113372 | 0.332449 | 0.161134 | 0.172433 | 0.292859 | 0.177576 | 0.302716 | 0.0971885 |
| Sports | 742645 | 458996 | 266832 | 573957 | 6.60366e+06 | 4.45716e+06 | 2.1465e+06 | 0.193905 | 0.324824 | 0.186684 | 0.214881 | 0.339284 | 0.16732 | 0.327671 | 0.109384 |
| Start | 59059 | 38288 | 22794 | 45209 | 446297 | 312161 | 134136 | 0.230121 | 0.313004 | 0.206969 | 0.200604 | 0.350708 | 0.167122 | 0.333037 | 0.107829 |
| Style | 30611 | 17243 | 10890 | 24054 | 237133 | 168395 | 68738 | 0.243311 | 0.308834 | 0.215343 | 0.200113 | 0.356988 | 0.164729 | 0.338478 | 0.105355 |
| Tests | 14585 | 8163 | 5413 | 11604 | 99542 | 73441 | 26101 | 0.273632 | 0.299688 | 0.232909 | 0.189377 | 0.372153 | 0.161816 | 0.347195 | 0.102294 |
| Total | 2638 | 2185 | 922 | 1915 | 17354 | 9336 | 8018 | 0.0677697 | 0.307287 | 0.101905 | 0.181823 | 0.258732 | 0.179005 | 0.266231 | 0.113323 |
| Travel | 84136 | 55950 | 32431 | 63101 | 614135 | 404586 | 209549 | 0.193893 | 0.312513 | 0.182973 | 0.194645 | 0.324123 | 0.173787 | 0.313055 | 0.111405 |
| Your SPIEGEL | 453 | 242 | 148 | 312 | 3310 | 2196 | 1114 | 0.182085 | 0.294054 | 0.177125 | 0.172745 | 0.294835 | 0.180338 | 0.293339 | 0.109939 |
Linear Regression Analysis: Evidence_uncongeniality_simplest_model_linear_regression_only_valence_non_standardized
```
Independent Variables: ['valence']
Dependent Variable: number O(n+1)-replies
Data: data_order0
Standardize: False
Report effect size: True
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.077
Model: OLS Adj. R-squared: 0.077
Method: Least Squares F-statistic: 4.005e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:42 Log-Likelihood: -8.5881e+06
No. Observations: 4786218 AIC: 1.718e+07
Df Residuals: 4786216 BIC: 1.718e+07
Df Model: 1
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [0.025 0.975]
------------------------------------------------------------------------------
const 1.4225 0.001 1845.132 0.000 1.421 1.424
valence -1.3913 0.002 -632.878 0.000 -1.396 -1.387
==============================================================================
Omnibus: 2883084.941 Durbin-Watson: 1.828
Prob(Omnibus): 0.000 Jarque-Bera (JB): 98618092.392
Skew: 2.349 Prob(JB): 0.00
Kurtosis: 24.736 Cond. No. 3.42
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongeniality_preregistered_model
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_order0
Standardize: True
Report effect size: True
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.220
Model: OLS Adj. R-squared: 0.220
Method: Least Squares F-statistic: 6.744e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:43 Log-Likelihood: -8.1863e+06
No. Observations: 4786218 AIC: 1.637e+07
Df Residuals: 4786215 BIC: 1.637e+07
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.1760 0.001 1922.382 0.000 1.175 1.177
bayes-corrected (q=0.25) valence -0.4349 0.001 -707.468 0.000 -0.436 -0.434
totalvotes 0.5207 0.001 847.067 0.000 0.520 0.522
==============================================================================
Omnibus: 2282674.662 Durbin-Watson: 1.758
Prob(Omnibus): 0.000 Jarque-Bera (JB): 64040137.713
Skew: 1.723 Prob(JB): 0.00
Kurtosis: 20.586 Cond. No. 1.10
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongeniality_stability_against_variation_in_weight_q5
```
Independent Variables: ['bayes-corrected (q=0.5) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_order0
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.229
Model: OLS Adj. R-squared: 0.229
Method: Least Squares F-statistic: 7.096e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:44 Log-Likelihood: -8.1590e+06
No. Observations: 4786218 AIC: 1.632e+07
Df Residuals: 4786215 BIC: 1.632e+07
Df Model: 2
Covariance Type: nonrobust
===================================================================================================
coef std err t P>|t| [0.025 0.975]
---------------------------------------------------------------------------------------------------
const 1.1760 0.001 1933.368 0.000 1.175 1.177
bayes-corrected (q=0.5) valence -0.4582 0.001 -749.070 0.000 -0.459 -0.457
totalvotes 0.5147 0.001 841.341 0.000 0.513 0.516
==============================================================================
Omnibus: 2271398.527 Durbin-Watson: 1.760
Prob(Omnibus): 0.000 Jarque-Bera (JB): 63503192.358
Skew: 1.712 Prob(JB): 0.00
Kurtosis: 20.513 Cond. No. 1.11
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongeniality_stability_against_variation_in_weight_q75
```
Independent Variables: ['bayes-corrected (q=0.75) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_order0
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.236
Model: OLS Adj. R-squared: 0.236
Method: Least Squares F-statistic: 7.380e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:45 Log-Likelihood: -8.1372e+06
No. Observations: 4786218 AIC: 1.627e+07
Df Residuals: 4786215 BIC: 1.627e+07
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.1760 0.001 1942.187 0.000 1.175 1.177
bayes-corrected (q=0.75) valence -0.4762 0.001 -781.029 0.000 -0.477 -0.475
totalvotes 0.5081 0.001 833.387 0.000 0.507 0.509
==============================================================================
Omnibus: 2256599.632 Durbin-Watson: 1.761
Prob(Omnibus): 0.000 Jarque-Bera (JB): 62251699.550
Skew: 1.700 Prob(JB): 0.00
Kurtosis: 20.338 Cond. No. 1.12
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongeniality_stability_against_variation_in_weight__no_bayes_correction
```
Independent Variables: ['valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_order0
Standardize: True
Report effect size: False
```
```
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.
```
Grouped Regression Analysis: Evidence_uncongeniality_robustness_analysis_on_person_level
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_order0
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Grouped by: user_id
Aggregation methods: {'bayes-corrected (q=0.25) valence': 'mean', 'totalvotes': 'sum', 'number O(n+1)-replies': 'sum'}
Standardize: True
Report effect size: False
Print detailed coefficients: True
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.934
Model: OLS Adj. R-squared: 0.934
Method: Least Squares F-statistic: 9.416e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:47 Log-Likelihood: -7.2556e+05
No. Observations: 133441 AIC: 1.451e+06
Df Residuals: 133438 BIC: 1.451e+06
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 42.4546 0.152 278.870 0.000 42.156 42.753
bayes-corrected (q=0.25) valence -3.7792 0.152 -24.824 0.000 -4.078 -3.481
totalvotes 208.8619 0.152 1371.920 0.000 208.564 209.160
==============================================================================
Omnibus: 253518.796 Durbin-Watson: 1.996
Prob(Omnibus): 0.000 Jarque-Bera (JB): 10401556910.024
Skew: 13.456 Prob(JB): 0.00
Kurtosis: 1370.496 Cond. No. 1.01
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
```
const: 42.4545829243 (CI: [ 42.1561998015, 42.7529660471])
```
```
bayes-corrected (q=0.25) valence: -3.7791674082 (CI: [-4.0775562969, -3.4807785195])
```
```
totalvotes: 208.8619281171 (CI: [ 208.5635392284, 209.1603170058])
```
Grouped Regression Analysis: Evidence_uncongeniality_robustness_analysis_on_section_level
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_order0
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Grouped by: section
Aggregation methods: {'bayes-corrected (q=0.25) valence': 'mean', 'totalvotes': 'sum', 'number O(n+1)-replies': 'sum'}
Standardize: True
Report effect size: False
Print detailed coefficients: True
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.959
Model: OLS Adj. R-squared: 0.955
Method: Least Squares F-statistic: 268.1
Date: Mon, 22 Jul 2024 Prob (F-statistic): 1.16e-16
Time: 09:31:47 Log-Likelihood: -334.54
No. Observations: 26 AIC: 675.1
Df Residuals: 23 BIC: 678.9
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 2.598e+05 1.95e+04 13.297 0.000 2.19e+05 3e+05
bayes-corrected (q=0.25) valence -4.206e+04 1.98e+04 -2.129 0.044 -8.29e+04 -1190.281
totalvotes 4.443e+05 1.98e+04 22.488 0.000 4.03e+05 4.85e+05
==============================================================================
Omnibus: 25.218 Durbin-Watson: 1.928
Prob(Omnibus): 0.000 Jarque-Bera (JB): 48.147
Skew: 1.909 Prob(JB): 3.51e-11
Kurtosis: 8.465 Cond. No. 1.16
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
```
const: 259811.1538461538 (CI: [ 219391.7551783801, 300230.5525139275])
```
```
bayes-corrected (q=0.25) valence: -42061.3741960863 (CI: [-82932.4677944659, -1190.2805977067])
```
```
totalvotes: 444292.7728500224 (CI: [ 403421.6792516428, 485163.8664484020])
```
Linear Regression Analysis: Evidence_uncongenialty_section_politics
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_politics
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.209
Model: OLS Adj. R-squared: 0.209
Method: Least Squares F-statistic: 1.708e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -2.1743e+06
No. Observations: 1295105 AIC: 4.349e+06
Df Residuals: 1295102 BIC: 4.349e+06
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.1182 0.001 981.264 0.000 1.116 1.120
bayes-corrected (q=0.25) valence -0.3909 0.001 -341.822 0.000 -0.393 -0.389
totalvotes 0.5079 0.001 444.124 0.000 0.506 0.510
==============================================================================
Omnibus: 680589.819 Durbin-Watson: 1.782
Prob(Omnibus): 0.000 Jarque-Bera (JB): 49094495.451
Skew: 1.699 Prob(JB): 0.00
Kurtosis: 32.971 Cond. No. 1.09
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_affairs
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_foreign_affairs
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.237
Model: OLS Adj. R-squared: 0.237
Method: Least Squares F-statistic: 1.380e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -1.5539e+06
No. Observations: 890221 AIC: 3.108e+06
Df Residuals: 890218 BIC: 3.108e+06
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.1789 0.001 802.397 0.000 1.176 1.182
bayes-corrected (q=0.25) valence -0.4979 0.001 -337.303 0.000 -0.501 -0.495
totalvotes 0.5435 0.001 368.179 0.000 0.541 0.546
==============================================================================
Omnibus: 415616.007 Durbin-Watson: 1.775
Prob(Omnibus): 0.000 Jarque-Bera (JB): 8567668.092
Skew: 1.765 Prob(JB): 0.00
Kurtosis: 17.782 Cond. No. 1.10
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_science
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_science
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.253
Model: OLS Adj. R-squared: 0.253
Method: Least Squares F-statistic: 9.746e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -1.0810e+06
No. Observations: 575190 AIC: 2.162e+06
Df Residuals: 575187 BIC: 2.162e+06
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.6458 0.002 787.663 0.000 1.642 1.650
bayes-corrected (q=0.25) valence -0.3951 0.002 -184.289 0.000 -0.399 -0.391
totalvotes 0.7495 0.002 349.574 0.000 0.745 0.754
==============================================================================
Omnibus: 194870.309 Durbin-Watson: 1.765
Prob(Omnibus): 0.000 Jarque-Bera (JB): 1100608.449
Skew: 1.527 Prob(JB): 0.00
Kurtosis: 9.050 Cond. No. 1.26
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_economy
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_economy
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.196
Model: OLS Adj. R-squared: 0.196
Method: Least Squares F-statistic: 7.576e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -1.0058e+06
No. Observations: 620776 AIC: 2.012e+06
Df Residuals: 620773 BIC: 2.012e+06
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.1396 0.002 734.230 0.000 1.137 1.143
bayes-corrected (q=0.25) valence -0.3478 0.002 -223.518 0.000 -0.351 -0.345
totalvotes 0.4695 0.002 301.664 0.000 0.466 0.473
==============================================================================
Omnibus: 202475.900 Durbin-Watson: 1.799
Prob(Omnibus): 0.000 Jarque-Bera (JB): 1088427.374
Skew: 1.479 Prob(JB): 0.00
Kurtosis: 8.773 Cond. No. 1.08
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_miscellaneous
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_miscellaneous
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.246
Model: OLS Adj. R-squared: 0.246
Method: Least Squares F-statistic: 7.921e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -8.1045e+05
No. Observations: 485006 AIC: 1.621e+06
Df Residuals: 485003 BIC: 1.621e+06
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.1141 0.002 602.981 0.000 1.110 1.118
bayes-corrected (q=0.25) valence -0.4406 0.002 -237.533 0.000 -0.444 -0.437
totalvotes 0.5508 0.002 296.904 0.000 0.547 0.554
==============================================================================
Omnibus: 308614.044 Durbin-Watson: 1.795
Prob(Omnibus): 0.000 Jarque-Bera (JB): 33388300.741
Skew: 2.187 Prob(JB): 0.00
Kurtosis: 43.411 Cond. No. 1.09
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_culture
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_culture
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.243
Model: OLS Adj. R-squared: 0.243
Method: Least Squares F-statistic: 3.781e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -3.6290e+05
No. Observations: 235911 AIC: 7.258e+05
Df Residuals: 235908 BIC: 7.258e+05
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 0.9173 0.002 395.396 0.000 0.913 0.922
bayes-corrected (q=0.25) valence -0.3334 0.002 -142.771 0.000 -0.338 -0.329
totalvotes 0.5075 0.002 217.346 0.000 0.503 0.512
==============================================================================
Omnibus: 99947.806 Durbin-Watson: 1.805
Prob(Omnibus): 0.000 Jarque-Bera (JB): 886847.368
Skew: 1.813 Prob(JB): 0.00
Kurtosis: 11.779 Cond. No. 1.12
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_sports
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_sports
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.256
Model: OLS Adj. R-squared: 0.256
Method: Least Squares F-statistic: 3.965e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -3.4768e+05
No. Observations: 230524 AIC: 6.954e+05
Df Residuals: 230521 BIC: 6.954e+05
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 0.8891 0.002 390.420 0.000 0.885 0.894
bayes-corrected (q=0.25) valence -0.3918 0.002 -171.548 0.000 -0.396 -0.387
totalvotes 0.4784 0.002 209.473 0.000 0.474 0.483
==============================================================================
Omnibus: 109314.794 Durbin-Watson: 1.837
Prob(Omnibus): 0.000 Jarque-Bera (JB): 1540320.347
Skew: 1.926 Prob(JB): 0.00
Kurtosis: 15.063 Cond. No. 1.08
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_mobility
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_mobility
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.198
Model: OLS Adj. R-squared: 0.198
Method: Least Squares F-statistic: 1.449e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -1.9705e+05
No. Observations: 117051 AIC: 3.941e+05
Df Residuals: 117048 BIC: 3.941e+05
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.3476 0.004 353.887 0.000 1.340 1.355
bayes-corrected (q=0.25) valence -0.3144 0.004 -80.973 0.000 -0.322 -0.307
totalvotes 0.5090 0.004 131.111 0.000 0.501 0.517
==============================================================================
Omnibus: 32287.766 Durbin-Watson: 1.796
Prob(Omnibus): 0.000 Jarque-Bera (JB): 111823.546
Skew: 1.377 Prob(JB): 0.00
Kurtosis: 6.917 Cond. No. 1.22
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_internet
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_internet
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.256
Model: OLS Adj. R-squared: 0.256
Method: Least Squares F-statistic: 2.267e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -2.1421e+05
No. Observations: 131977 AIC: 4.284e+05
Df Residuals: 131974 BIC: 4.284e+05
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.0804 0.003 320.014 0.000 1.074 1.087
bayes-corrected (q=0.25) valence -0.4040 0.003 -118.355 0.000 -0.411 -0.397
totalvotes 0.5375 0.003 157.450 0.000 0.531 0.544
==============================================================================
Omnibus: 54168.298 Durbin-Watson: 1.825
Prob(Omnibus): 0.000 Jarque-Bera (JB): 590918.640
Skew: 1.674 Prob(JB): 0.00
Kurtosis: 12.811 Cond. No. 1.16
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongenialty_section_health
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_health
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.257
Model: OLS Adj. R-squared: 0.257
Method: Least Squares F-statistic: 8576.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:48 Log-Likelihood: -86794.
No. Observations: 49462 AIC: 1.736e+05
Df Residuals: 49459 BIC: 1.736e+05
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 1.3371 0.006 212.544 0.000 1.325 1.349
bayes-corrected (q=0.25) valence -0.4685 0.006 -73.917 0.000 -0.481 -0.456
totalvotes 0.6228 0.006 98.259 0.000 0.610 0.635
==============================================================================
Omnibus: 17663.533 Durbin-Watson: 1.771
Prob(Omnibus): 0.000 Jarque-Bera (JB): 106942.347
Skew: 1.595 Prob(JB): 0.00
Kurtosis: 9.459 Cond. No. 1.13
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncongeniality_robustness_order1
```
Independent Variables: ['bayes-corrected (q=0.25) valence', 'totalvotes']
Dependent Variable: number O(n+1)-replies
Data: data_order1
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.136
Model: OLS Adj. R-squared: 0.136
Method: Least Squares F-statistic: 3.982e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:50 Log-Likelihood: -6.2998e+06
No. Observations: 5050120 AIC: 1.260e+07
Df Residuals: 5050117 BIC: 1.260e+07
Df Model: 2
Covariance Type: nonrobust
====================================================================================================
coef std err t P>|t| [0.025 0.975]
----------------------------------------------------------------------------------------------------
const 0.6133 0.000 1636.095 0.000 0.613 0.614
bayes-corrected (q=0.25) valence -0.2055 0.000 -548.027 0.000 -0.206 -0.205
totalvotes 0.2575 0.000 686.512 0.000 0.257 0.258
==============================================================================
Omnibus: 2832727.339 Durbin-Watson: 1.864
Prob(Omnibus): 0.000 Jarque-Bera (JB): 85433368.019
Skew: 2.153 Prob(JB): 0.00
Kurtosis: 22.684 Cond. No. 1.03
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_uncogeniality_model_with_seperate_upvotes_downvotes
```
Independent Variables: ['upvotes', 'downvotes']
Dependent Variable: number O(n+1)-replies
Data: data_order0
Standardize: True
Report effect size: False
```
```
OLS Regression Results
=================================================================================
Dep. Variable: number O(n+1)-replies R-squared: 0.194
Model: OLS Adj. R-squared: 0.194
Method: Least Squares F-statistic: 7.311e+05
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:51 Log-Likelihood: -1.0415e+07
No. Observations: 6069971 AIC: 2.083e+07
Df Residuals: 6069968 BIC: 2.083e+07
Df Model: 2
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [0.025 0.975]
------------------------------------------------------------------------------
const 1.1129 0.001 2037.629 0.000 1.112 1.114
upvotes 0.0893 0.001 162.278 0.000 0.088 0.090
downvotes 0.6433 0.001 1168.654 0.000 0.642 0.644
==============================================================================
Omnibus: 3179849.625 Durbin-Watson: 1.812
Prob(Omnibus): 0.000 Jarque-Bera (JB): 138815450.026
Skew: 1.836 Prob(JB): 0.00
Kurtosis: 26.138 Cond. No. 1.13
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_preregistered_model
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_order0
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.021
Model: OLS Adj. R-squared: 0.021
Method: Least Squares F-statistic: 5.020e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:51 Log-Likelihood: -221.34
No. Observations: 2392896 AIC: 446.7
Df Residuals: 2392894 BIC: 472.1
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1246 0.000 796.722 0.000 0.124 0.125
mean bayes-corrected (q=0.25) valence of replies -0.0351 0.000 -224.063 0.000 -0.035 -0.035
==============================================================================
Omnibus: 426104.077 Durbin-Watson: 1.729
Prob(Omnibus): 0.000 Jarque-Bera (JB): 131391.270
Skew: -0.336 Prob(JB): 0.00
Kurtosis: 2.070 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_stability_against_variation_in_weight_q5
```
Independent Variables: ['mean bayes-corrected (q=0.5) valence of replies']
Dependent Variable: bayes-corrected (q=0.5) valence
Data: data_order0
Standardize: True
Report effect size: False
```
```
OLS Regression Results
===========================================================================================
Dep. Variable: bayes-corrected (q=0.5) valence R-squared: 0.027
Model: OLS Adj. R-squared: 0.027
Method: Least Squares F-statistic: 6.556e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:52 Log-Likelihood: 3.9215e+05
No. Observations: 2392896 AIC: -7.843e+05
Df Residuals: 2392894 BIC: -7.843e+05
Df Model: 1
Covariance Type: nonrobust
===================================================================================================================
coef std err t P>|t| [0.025 0.975]
-------------------------------------------------------------------------------------------------------------------
const 0.1323 0.000 996.732 0.000 0.132 0.133
mean bayes-corrected (q=0.5) valence of replies -0.0340 0.000 -256.042 0.000 -0.034 -0.034
==============================================================================
Omnibus: 168653.316 Durbin-Watson: 1.726
Prob(Omnibus): 0.000 Jarque-Bera (JB): 107460.980
Skew: -0.396 Prob(JB): 0.00
Kurtosis: 2.328 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_stability_against_variation_in_weight_q75
```
Independent Variables: ['mean bayes-corrected (q=0.75) valence of replies']
Dependent Variable: bayes-corrected (q=0.75) valence
Data: data_order0
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.75) valence R-squared: 0.032
Model: OLS Adj. R-squared: 0.032
Method: Least Squares F-statistic: 8.012e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:52 Log-Likelihood: 8.8112e+05
No. Observations: 2392896 AIC: -1.762e+06
Df Residuals: 2392894 BIC: -1.762e+06
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1411 0.000 1303.270 0.000 0.141 0.141
mean bayes-corrected (q=0.75) valence of replies -0.0306 0.000 -283.054 0.000 -0.031 -0.030
==============================================================================
Omnibus: 95205.666 Durbin-Watson: 1.729
Prob(Omnibus): 0.000 Jarque-Bera (JB): 102788.717
Skew: -0.491 Prob(JB): 0.00
Kurtosis: 2.742 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_stability_against_variation_in_weight_no_bayes_correction
```
Independent Variables: ['mean valence of replies']
Dependent Variable: valence
Data: data_order0
Standardize: True
Report effect size: False
```
```
OLS Regression Results
==============================================================================
Dep. Variable: valence R-squared: 0.010
Model: OLS Adj. R-squared: 0.010
Method: Least Squares F-statistic: 2.337e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:53 Log-Likelihood: -4.8218e+05
No. Observations: 2392896 AIC: 9.644e+05
Df Residuals: 2392894 BIC: 9.644e+05
Df Model: 1
Covariance Type: nonrobust
===========================================================================================
coef std err t P>|t| [0.025 0.975]
-------------------------------------------------------------------------------------------
const 0.1158 0.000 604.951 0.000 0.115 0.116
mean valence of replies -0.0293 0.000 -152.877 0.000 -0.030 -0.029
==============================================================================
Omnibus: 785394.853 Durbin-Watson: 1.750
Prob(Omnibus): 0.000 Jarque-Bera (JB): 152455.997
Skew: -0.323 Prob(JB): 0.00
Kurtosis: 1.946 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_politics
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_politics
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.018
Model: OLS Adj. R-squared: 0.018
Method: Least Squares F-statistic: 1.166e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:53 Log-Likelihood: 34045.
No. Observations: 621929 AIC: -6.809e+04
Df Residuals: 621927 BIC: -6.806e+04
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1305 0.000 449.326 0.000 0.130 0.131
mean bayes-corrected (q=0.25) valence of replies -0.0314 0.000 -107.983 0.000 -0.032 -0.031
==============================================================================
Omnibus: 78154.602 Durbin-Watson: 1.733
Prob(Omnibus): 0.000 Jarque-Bera (JB): 31765.731
Skew: -0.357 Prob(JB): 0.00
Kurtosis: 2.155 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_affairs
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_foreign_affairs
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.019
Model: OLS Adj. R-squared: 0.019
Method: Least Squares F-statistic: 8343.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:53 Log-Likelihood: -43060.
No. Observations: 440260 AIC: 8.612e+04
Df Residuals: 440258 BIC: 8.615e+04
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1353 0.000 336.404 0.000 0.134 0.136
mean bayes-corrected (q=0.25) valence of replies -0.0367 0.000 -91.341 0.000 -0.038 -0.036
==============================================================================
Omnibus: 129058.321 Durbin-Watson: 1.735
Prob(Omnibus): 0.000 Jarque-Bera (JB): 32315.635
Skew: -0.421 Prob(JB): 0.00
Kurtosis: 1.974 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_science
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_science
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.028
Model: OLS Adj. R-squared: 0.028
Method: Least Squares F-statistic: 1.007e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:53 Log-Likelihood: 27583.
No. Observations: 345534 AIC: -5.516e+04
Df Residuals: 345532 BIC: -5.514e+04
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.0723 0.000 190.132 0.000 0.072 0.073
mean bayes-corrected (q=0.25) valence of replies -0.0381 0.000 -100.372 0.000 -0.039 -0.037
==============================================================================
Omnibus: 59103.072 Durbin-Watson: 1.791
Prob(Omnibus): 0.000 Jarque-Bera (JB): 12955.369
Skew: -0.052 Prob(JB): 0.00
Kurtosis: 2.057 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_economy
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_economy
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.017
Model: OLS Adj. R-squared: 0.017
Method: Least Squares F-statistic: 5484.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:53 Log-Likelihood: 24023.
No. Observations: 316428 AIC: -4.804e+04
Df Residuals: 316426 BIC: -4.802e+04
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1474 0.000 369.619 0.000 0.147 0.148
mean bayes-corrected (q=0.25) valence of replies -0.0295 0.000 -74.054 0.000 -0.030 -0.029
==============================================================================
Omnibus: 28321.195 Durbin-Watson: 1.760
Prob(Omnibus): 0.000 Jarque-Bera (JB): 17536.904
Skew: -0.450 Prob(JB): 0.00
Kurtosis: 2.278 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_miscellaneous
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_miscellaneous
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.028
Model: OLS Adj. R-squared: 0.028
Method: Least Squares F-statistic: 6790.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:54 Log-Likelihood: -13916.
No. Observations: 235551 AIC: 2.784e+04
Df Residuals: 235549 BIC: 2.786e+04
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1362 0.001 257.499 0.000 0.135 0.137
mean bayes-corrected (q=0.25) valence of replies -0.0436 0.001 -82.403 0.000 -0.045 -0.043
==============================================================================
Omnibus: 52959.753 Durbin-Watson: 1.732
Prob(Omnibus): 0.000 Jarque-Bera (JB): 15867.344
Skew: -0.409 Prob(JB): 0.00
Kurtosis: 2.027 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_culture
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_culture
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.032
Model: OLS Adj. R-squared: 0.032
Method: Least Squares F-statistic: 3435.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:54 Log-Likelihood: -1315.0
No. Observations: 102305 AIC: 2634.
Df Residuals: 102303 BIC: 2653.
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1253 0.001 163.518 0.000 0.124 0.127
mean bayes-corrected (q=0.25) valence of replies -0.0449 0.001 -58.610 0.000 -0.046 -0.043
==============================================================================
Omnibus: 19234.419 Durbin-Watson: 1.748
Prob(Omnibus): 0.000 Jarque-Bera (JB): 5689.759
Skew: -0.334 Prob(JB): 0.00
Kurtosis: 2.057 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_sports
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_sports
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.032
Model: OLS Adj. R-squared: 0.032
Method: Least Squares F-statistic: 3344.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:54 Log-Likelihood: -6723.8
No. Observations: 100071 AIC: 1.345e+04
Df Residuals: 100069 BIC: 1.347e+04
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1246 0.001 152.318 0.000 0.123 0.126
mean bayes-corrected (q=0.25) valence of replies -0.0473 0.001 -57.827 0.000 -0.049 -0.046
==============================================================================
Omnibus: 28267.899 Durbin-Watson: 1.740
Prob(Omnibus): 0.000 Jarque-Bera (JB): 6368.870
Skew: -0.345 Prob(JB): 0.00
Kurtosis: 1.975 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_mobility
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_mobility
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.024
Model: OLS Adj. R-squared: 0.024
Method: Least Squares F-statistic: 1726.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:54 Log-Likelihood: 10825.
No. Observations: 69253 AIC: -2.165e+04
Df Residuals: 69251 BIC: -2.163e+04
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1109 0.001 141.050 0.000 0.109 0.112
mean bayes-corrected (q=0.25) valence of replies -0.0327 0.001 -41.551 0.000 -0.034 -0.031
==============================================================================
Omnibus: 6922.840 Durbin-Watson: 1.814
Prob(Omnibus): 0.000 Jarque-Bera (JB): 2381.203
Skew: -0.195 Prob(JB): 0.00
Kurtosis: 2.179 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_internet
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_internet
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.028
Model: OLS Adj. R-squared: 0.028
Method: Least Squares F-statistic: 1805.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:54 Log-Likelihood: -3477.5
No. Observations: 63079 AIC: 6959.
Df Residuals: 63077 BIC: 6977.
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1191 0.001 117.001 0.000 0.117 0.121
mean bayes-corrected (q=0.25) valence of replies -0.0433 0.001 -42.490 0.000 -0.045 -0.041
==============================================================================
Omnibus: 21454.701 Durbin-Watson: 1.721
Prob(Omnibus): 0.000 Jarque-Bera (JB): 4028.801
Skew: -0.319 Prob(JB): 0.00
Kurtosis: 1.939 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_section_health
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_health
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.043
Model: OLS Adj. R-squared: 0.043
Method: Least Squares F-statistic: 1211.
Date: Mon, 22 Jul 2024 Prob (F-statistic): 1.61e-259
Time: 09:31:54 Log-Likelihood: -439.22
No. Observations: 27005 AIC: 882.4
Df Residuals: 27003 BIC: 898.9
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1074 0.001 71.776 0.000 0.104 0.110
mean bayes-corrected (q=0.25) valence of replies -0.0521 0.001 -34.794 0.000 -0.055 -0.049
==============================================================================
Omnibus: 6746.889 Durbin-Watson: 1.761
Prob(Omnibus): 0.000 Jarque-Bera (JB): 1324.435
Skew: -0.197 Prob(JB): 2.53e-288
Kurtosis: 1.989 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Linear Regression Analysis: Evidence_antagonism_robustness_order1
```
Independent Variables: ['mean bayes-corrected (q=0.25) valence of replies']
Dependent Variable: bayes-corrected (q=0.25) valence
Data: data_order1
Standardize: True
Report effect size: False
```
```
OLS Regression Results
============================================================================================
Dep. Variable: bayes-corrected (q=0.25) valence R-squared: 0.057
Model: OLS Adj. R-squared: 0.057
Method: Least Squares F-statistic: 9.915e+04
Date: Mon, 22 Jul 2024 Prob (F-statistic): 0.00
Time: 09:31:54 Log-Likelihood: 2.1429e+05
No. Observations: 1630262 AIC: -4.286e+05
Df Residuals: 1630260 BIC: -4.286e+05
Df Model: 1
Covariance Type: nonrobust
====================================================================================================================
coef std err t P>|t| [0.025 0.975]
--------------------------------------------------------------------------------------------------------------------
const 0.1419 0.000 854.072 0.000 0.142 0.142
mean bayes-corrected (q=0.25) valence of replies -0.0523 0.000 -314.877 0.000 -0.053 -0.052
==============================================================================
Omnibus: 101738.374 Durbin-Watson: 1.753
Prob(Omnibus): 0.000 Jarque-Bera (JB): 62821.338
Skew: -0.351 Prob(JB): 0.00
Kurtosis: 2.343 Cond. No. 1.00
==============================================================================
Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_order0
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.28634078314814315
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.31853427098636283
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.12461005214018245
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09803757310470287
Degrees of Freedom: 2392895
Cohen's d: -0.28714996199978216
T-statistic: -396.76675511778956
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_stability_against_variation_in_weight_paired_ttest_q5
```
Variable 1: bayes-corrected (q=0.5) extremity
Variable 2: mean bayes-corrected (q=0.5) extremity of replies
Data: data_order0
```
```
Mean of bayes-corrected (q=0.5) extremity: 0.2934997056888845
Mean of mean bayes-corrected (q=0.5) extremity of replies: 0.31880240669265064
Standard Deviation of bayes-corrected (q=0.5) extremity: 0.10366027656607042
Standard Deviation of mean bayes-corrected (q=0.5) extremity of replies: 0.07259709613375841
Degrees of Freedom: 2392895
Cohen's d: -0.28275329909468133
T-statistic: -394.7125869249032
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_stability_against_variation_in_weight_paired_ttest_q75
```
Variable 1: bayes-corrected (q=0.75) extremity
Variable 2: mean bayes-corrected (q=0.75) extremity of replies
Data: data_order0
```
```
Mean of bayes-corrected (q=0.75) extremity: 0.3010823980840001
Mean of mean bayes-corrected (q=0.75) extremity of replies: 0.32039106933723704
Standard Deviation of bayes-corrected (q=0.75) extremity: 0.08248076963764756
Standard Deviation of mean bayes-corrected (q=0.75) extremity of replies: 0.05223289636934443
Degrees of Freedom: 2392895
Cohen's d: -0.2796984844303324
T-statistic: -391.6388789093796
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_stability_against_variation_in_weight_paired_ttest_bayes
```
Variable 1: extremity
Variable 2: mean extremity of replies
Data: data_order0
```
```
Mean of extremity: 0.2786279465660722
Mean of mean extremity of replies: 0.33064022086792666
Standard Deviation of extremity: 0.15566001726472525
Standard Deviation of mean extremity of replies: 0.15685179947476463
Degrees of Freedom: 2392895
Cohen's d: -0.332863548235494
T-statistic: -441.7826610833192
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_robustness_paired_ttest_order1
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_order1
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.29265411081901965
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.316766141686027
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.11701339959130957
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09812627267575441
Degrees of Freedom: 1630261
Cohen's d: -0.2232935227954181
T-statistic: -248.9875068375778
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_politics
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_politics
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.2747813213977206
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.31051648819461664
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.1232411698734475
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09815038738028235
Degrees of Freedom: 621928
Cohen's d: -0.3207697725588003
T-statistic: -224.4339595489235
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_foreign_affairs
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_foreign_affairs
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.30983360408913946
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.330913534598374
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.1266220167440838
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.0994658270407316
Degrees of Freedom: 440259
Cohen's d: -0.18514479506979328
T-statistic: -116.67457613500132
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_science
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_science
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.25732194943047365
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.3019777399435376
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.1187657730515952
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09498121080140695
Degrees of Freedom: 345533
Cohen's d: -0.4152747999524859
T-statistic: -212.56678640514008
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_economy
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_economy
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.28753090601867964
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.3206172046668397
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.12269603857552688
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09544219919767762
Degrees of Freedom: 316427
Cohen's d: -0.3010114266220678
T-statistic: -144.89599610520233
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_miscellaneous
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_miscellaneous
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.3045872088628839
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.33005502824126426
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.12405998014131653
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09742991339150692
Degrees of Freedom: 235550
Cohen's d: -0.22832386975048508
T-statistic: -97.05206575930157
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_culture
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_culture
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.2873043034163312
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.3180681433274033
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.12427097360816901
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.10041204122831116
Degrees of Freedom: 102304
Cohen's d: -0.27231114070182555
T-statistic: -77.26207861609845
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_sports
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_sports
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.30601102207250513
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.328439915246921
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.12292708240128108
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.098047183761713
Degrees of Freedom: 100070
Cohen's d: -0.20172544463043993
T-statistic: -55.9671976011527
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_mobility
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_mobility
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.25434099233474056
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.3002874727751491
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.1194543498720806
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09661488578718154
Degrees of Freedom: 69252
Cohen's d: -0.4229377864257918
T-statistic: -93.24696971910268
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_internet
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_internet
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.30568494651578504
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.33706126033387757
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.12135285517757544
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09268724557998224
Degrees of Freedom: 63078
Cohen's d: -0.2905871965145026
T-statistic: -63.21801300923011
P-value: 0.0
```
Paired TTest Analysis: Evidence_polarization_paired_ttest_extremity_health
```
Variable 1: bayes-corrected (q=0.25) extremity
Variable 2: mean bayes-corrected (q=0.25) extremity of replies
Data: data_health
```
```
Mean of bayes-corrected (q=0.25) extremity: 0.286001211119296
Mean of mean bayes-corrected (q=0.25) extremity of replies: 0.32344058185785135
Standard Deviation of bayes-corrected (q=0.25) extremity: 0.12360412242902419
Standard Deviation of mean bayes-corrected (q=0.25) extremity of replies: 0.09582069057098505
Degrees of Freedom: 27004
Cohen's d: -0.3385470290175242
T-statistic: -48.09524752175683
P-value: 0.0
```
Visualization: Fig_2a
```
Data: data_order0
Title: None
Creating Hexbin Plot
Variable X: bayes-corrected (q=0.25) valence
Variable Y: number O(n+1)-replies
X Axis Maximum: None
Y Axis Maximum: 40
Trendline: True
Log Scaling: True
```
Plot saved at results/Fig_2a.png
![](../results/Fig_2a.png)
Visualization: Fig_2b
```
Data: data
Title: None
Creating Forest Plot
Regression Model Names: ['Evidence_uncongenialty_section_politics', 'Evidence_uncongenialty_section_foreign_affairs', 'Evidence_uncongenialty_section_science', 'Evidence_uncongenialty_section_economy', 'Evidence_uncongenialty_section_miscellaneous', 'Evidence_uncongenialty_section_culture', 'Evidence_uncongenialty_section_sports', 'Evidence_uncongenialty_section_mobility', 'Evidence_uncongenialty_section_internet', 'Evidence_uncongenialty_section_health']
Coefficient Names: ['bayes-corrected (q=0.25) valence', 'totalvotes']
X-Axis Minimum: -0.6
X-Axis Maximum: None
Dotsize: 2
```
Plot saved at results/Fig_2b.png
![](../results/Fig_2b.png)
Visualization: Fig_2c
```
Data: data_order0_with_minimum_one_vote
Title: None
Creating Heatmap
Axis Variables: ['upvotes', 'downvotes']
Heat Variable: number O(n+1)-replies
Max Axis Values: [20, 20]
Min Axis Values: [0, 0]
Log Scaling: false
```
Plot saved at results/Fig_2c.png
![](../results/Fig_2c.png)
Visualization: Fig_3a
```
Data: data_order0
Title: None
Creating Density Plot
Variable X: mean bayes-corrected (q=0.25) valence of replies
Variable Y: bayes-corrected (q=0.25) valence
Data Breakpoints: [0]
```
Plot saved at results/Fig_3a.png
![](../results/Fig_3a.png)
Visualization: Fig_3b
```
Data: data
Title: None
Creating Forest Plot
Regression Model Names: ['Evidence_antagonism_section_politics', 'Evidence_antagonism_section_foreign_affairs', 'Evidence_antagonism_section_science', 'Evidence_antagonism_section_economy', 'Evidence_antagonism_section_miscellaneous', 'Evidence_antagonism_section_culture', 'Evidence_antagonism_section_sports', 'Evidence_antagonism_section_mobility', 'Evidence_antagonism_section_internet', 'Evidence_antagonism_section_health']
Coefficient Names: ['mean bayes-corrected (q=0.25) valence of replies']
X-Axis Minimum: -0.1
X-Axis Maximum: None
Dotsize: 2
```
Plot saved at results/Fig_3b.png
![](../results/Fig_3b.png)
Visualization: Fig_4a
```
Data: data_order0
Title:
Creating Violin Plot
Variable X: bayes-corrected (q=0.25) extremity
Variable Y: mean bayes-corrected (q=0.25) extremity of replies
X-Axis Label:
Y-Axis Label: Extremity value
```
Plot saved at results/Fig_4a.png
![](../results/Fig_4a.png)
Visualization: Fig_4b
```
Data: data
Title: None
Creating Forest Plot Paired TTest
Paired TTest Names: ['Evidence_polarization_paired_ttest_extremity_politics', 'Evidence_polarization_paired_ttest_extremity_affairs', 'Evidence_polarization_paired_ttest_extremity_science', 'Evidence_polarization_paired_ttest_extremity_economy', 'Evidence_polarization_paired_ttest_extremity_miscellaneous', 'Evidence_polarization_paired_ttest_extremity_culture', 'Evidence_polarization_paired_ttest_extremity_sports', 'Evidence_polarization_paired_ttest_extremity_mobility', 'Evidence_polarization_paired_ttest_extremity_internet', 'Evidence_polarization_paired_ttest_extremity_health']
X-Axis Minimum: -0.06
X-Axis Maximum: None
Dotsize: 2
```
Plot saved at results/Fig_4b.png
![](../results/Fig_4b.png)
Visualization: Extended_Fig_1
```
Data: data
Title:
Creating Histogram Plot
Variable: totalvotes
X-Axis Limits: None
X-Axis Logarithmic Scaling: False
Y-Axis Logarithmic Scaling: True
```
Plot saved at results/Extended_Fig_1.png
![](../results/Extended_Fig_1.png)
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