# 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)