```r users: 514437 condition N 1: c 257133 2: t 257304 period days 1: t0 24 2: t1 7 clustid tweets_in_clust 1: 0 2052740 2: 4 1100140 3: 6 189868 4: 7 19619 5: 8 681887 6: 9 1690166 7: 17 962410 ``` # models quasipoisson count model ```r # all tweets GLM estimation, family = quasipoisson, Dep. Var.: t1 Observations: 3,545,815 Fixed-effects: block: 12,287, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC -0.000864 0.006680 -0.129350 0.89708 # negative estimate but n.s. t0SC 0.490237 0.000883 555.105816 < 2.2e-16 *** conditionC:t0SC -0.000951 0.001260 -0.754479 0.45058 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Squared Cor.: 0.570692 # retweets only GLM estimation, family = quasipoisson, Dep. Var.: t1 Observations: 3,521,623 Fixed-effects: block: 12,001, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC -0.007949 0.007673 -1.035887 0.30028 # negative estimate but n.s. t0SC 0.500899 0.000986 508.239614 < 2.2e-16 *** conditionC:t0SC -0.000278 0.001326 -0.209793 0.83383 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Squared Cor.: 0.593457 # retweets only; without interaction > feglm(t1 ~ conditionC + t0SC | block + day, d3, family = "quasipoisson", cluster = "block") NOTE: 1,202/0 fixed-effects (79,436 observations) removed because of only 0 outcomes. GLM estimation, family = quasipoisson, Dep. Var.: t1 Observations: 3,521,623 Fixed-effects: block: 12,001, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC -0.00969 0.006400 -1.51408 0.13003 t0SC 0.50090 0.000986 508.26738 < 2.2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Squared Cor.: 0.593459 ``` linear probability model ```r # all tweets OLS estimation, Dep. Var.: t1bin Observations: 3,601,059 Fixed-effects: block: 13,203, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC 0.000726 0.000498 1.45912 0.14456 t0binSC 0.206638 0.000912 226.59257 < 2.2e-16 *** conditionC:t0binSC 0.001174 0.001017 1.15444 0.24834 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 RMSE: 0.305573 Adj. R2: 0.138594 Within R2: 0.095825 # retweets only OLS estimation, Dep. Var.: t1bin Observations: 3,601,059 Fixed-effects: block: 13,203, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC 0.000299 0.000561 0.532966 0.59407 t0binSC 0.206838 0.000970 213.147799 < 2.2e-16 *** conditionC:t0binSC 0.000725 0.001138 0.637152 0.52404 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 RMSE: 0.274783 Adj. R2: 0.155288 Within R2: 0.113745 ``` logistic regression ```r # all tweets GLM estimation, family = binomial, Dep. Var.: t1bin Observations: 3,545,787 Fixed-effects: block: 12,286, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC -0.001327 0.009011 -0.147305 0.88289 # negative estimate but n.s. t0binSC 3.233058 0.010569 305.892519 < 2.2e-16 *** conditionC:t0binSC 0.018268 0.018180 1.004813 0.31499 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Log-Likelihood: -1,050,815.9 Adj. Pseudo R2: 0.208951 BIC: 2,287,056.1 Squared Cor.: 0.160118 # retweets only GLM estimation, family = binomial, Dep. Var.: t1bin Observations: 3,521,595 Fixed-effects: block: 12,000, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC -0.011487 0.009646 -1.19089 0.23370 # negative estimate but n.s. t0binSC 3.531437 0.011169 316.18687 < 2.2e-16 *** conditionC:t0binSC 0.031746 0.019512 1.62699 0.10374 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Log-Likelihood: -853,721.1 Adj. Pseudo R2: 0.253249 BIC: 1,888,471.0 Squared Cor.: 0.182951 ``` # descriptives ```r # no. of users (in both conditions) who shared bad tweets per day d1[, .N, keyby = .(ymd, period)] ymd period N 1: 2023-03-24 0 66216 # t0 2: 2023-03-25 0 65812 3: 2023-03-26 0 65193 4: 2023-03-27 0 64198 5: 2023-03-28 0 70359 6: 2023-03-29 0 67636 7: 2023-03-30 0 72490 8: 2023-03-31 0 71532 9: 2023-04-01 0 67544 10: 2023-04-02 0 67302 11: 2023-04-03 0 63957 12: 2023-04-04 0 69728 13: 2023-04-05 0 69189 14: 2023-04-06 0 63429 15: 2023-04-07 0 62827 16: 2023-04-08 0 62128 17: 2023-04-09 0 59859 18: 2023-04-10 0 61157 19: 2023-04-11 0 59834 20: 2023-04-12 0 57851 21: 2023-04-13 0 63182 22: 2023-04-14 0 64408 23: 2023-04-15 0 69808 24: 2023-04-16 0 72291 25: 2023-04-17 1 69726 # t1 26: 2023-04-18 1 66242 27: 2023-04-19 1 60174 28: 2023-04-20 1 65045 29: 2023-04-21 1 63559 30: 2023-04-22 1 62203 31: 2023-04-23 1 60413 ymd period N ``` # models without interaction ```r > feols(t1bin ~ conditionC + t0binSC| block + day, d3, cluster = "block") OLS estimation, Dep. Var.: t1bin Observations: 3,601,059 Fixed-effects: block: 13,203, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC 0.000241 0.000475 0.507174 0.61204 t0binSC 0.206838 0.000970 213.148396 < 2.2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 RMSE: 0.274783 Adj. R2: 0.155288 Within R2: 0.113745 > feglm(t1bin ~ conditionC + t0binSC | block + day, family = "binomial", d3, cluster = "block") NOTE: 1,203/0 fixed-effects (79,464 observations) removed because of only 0 (or only 1) outcomes. GLM estimation, family = binomial, Dep. Var.: t1bin Observations: 3,521,595 Fixed-effects: block: 12,000, day: 7 Standard-errors: Clustered (block) Estimate Std. Error t value Pr(>|t|) conditionC 0.002361 0.006512 0.362538 0.71695 t0binSC 3.531350 0.011169 316.172953 < 2.2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Log-Likelihood: -853,723.0 Adj. Pseudo R2: 0.253248 BIC: 1,888,459.8 Squared Cor.: 0.18295 ```