SlowGuess/NAACL_2021_OCR huggingface dataset:
Table 30: Victim..Discrimination
countryEU	0.046*** (0.012)
countryGB	0.453*** (0.006)
has_hashtag1	-0.165*** (0.009)
has Mention1	-0.162*** (0.007)
has_url1	-0.103*** (0.009)
isQuote_status1	0.201*** (0.008)
is_reply1	0.173*** (0.008)
is_verified1	0.473*** (0.015)
log_chars	1.022*** (0.007)
log_followers	-0.151*** (0.002)
log_following	0.074*** (0.002)
log statuses	0.101*** (0.002)
Constant	-8.099*** (0.058)
Observations	2,661,435
Log Likelihood	-770,001.000
Akaike Inf. Crit.	1,540,034.000
Bayesian Inf. Crit.	1,540,239.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 28: Threat..National.Cohesion
countryEU	0.279*** (0.012)
countryGB	0.083*** (0.008)
has_hashtag1	0.117*** (0.009)
has Mention1	0.067*** (0.009)
has_url1	-0.372*** (0.009)
isQuote_status1	0.863*** (0.008)
is_reply1	0.631*** (0.009)
is_verified1	-1.817*** (0.035)
log_chars	0.643*** (0.007)
log_followers	0.040*** (0.003)
log_following	-0.003 (0.003)
log statuses	-0.028*** (0.002)
Constant	-6.122*** (0.061)
Observations	2,661,435
Log Likelihood	-659,886.300
Akaike Inf. Crit.	1,319,805.000
Bayesian Inf. Crit.	1,320,009.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 31: Victim..Global.Economy
countryEU	0.914*** (0.033)
countryGB	1.088*** (0.019)
has_hashtag1	-0.344*** (0.036)
has Mention1	0.018 (0.029)
has_url1	0.015 (0.033)
isQuote_status1	0.213*** (0.031)
is_reply1	0.387*** (0.029)
is_verified1	0.272*** (0.057)
log_chars	0.603*** (0.024)
log_followers	-0.059*** (0.008)
log_following	-0.004 (0.008)
log statuses	-0.015** (0.006)
Constant	-8.433*** (0.130)
Observations	2,661,435
Log Likelihood	-94,328.800
Akaike Inf. Crit.	188,689.600
Bayesian Inf. Crit.	188,894.300
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 29: Threat..Public.Order
countryEU	-0.675*** (0.009)
countryGB	-1.381*** (0.007)
has_hashtag1	0.053*** (0.005)
has Mention1	0.216*** (0.005)
has_url1	0.029*** (0.005)
isQuote_status1	0.448*** (0.005)
is_reply1	0.244*** (0.005)
is_verified1	-1.226*** (0.013)
log_chars	0.274*** (0.004)
log_followers	0.006*** (0.001)
log_following	0.045*** (0.002)
log statuses	-0.012*** (0.001)
Constant	-2.966*** (0.056)
Observations	2,661,435
Log Likelihood	-1,469,478.000
Akaike Inf. Crit.	2,938,987.000
Bayesian Inf. Crit.	2,939,192.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 32: Victim..Humanitarian
countryEU	-0.059*** (0.013)
countryGB	-0.453*** (0.009)
has_hashtag1	0.198*** (0.007)
has Mention1	-0.339*** (0.007)
has_url1	0.534*** (0.010)
isQuote_status1	-0.306*** (0.008)
is_reply1	-0.570*** (0.008)
is_verified1	0.553*** (0.013)
log_chars	0.473*** (0.007)
log_followers	-0.048*** (0.002)
log_following	0.033*** (0.002)
log statuses	0.045*** (0.002)
Constant	-5.456*** (0.098)
Observations	2,661,435
Log Likelihood	-679,409.600
Akaike Inf. Crit.	1,358,851.000
Bayesian Inf. Crit.	1,359,056.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 33: Victim..War
countryEU	0.631*** (0.046)
countryGB	0.228*** (0.033)
has_hashtag1	-0.135*** (0.042)
has Mention1	-0.596*** (0.036)
has_url1	0.529*** (0.058)
isQuote_status1	-0.144*** (0.039)
is_reply1	0.274*** (0.038)
is_verified1	0.612*** (0.060)
log_chars	1.017*** (0.033)
log_followers	-0.062*** (0.010)
log_following	0.015 (0.011)
log statuses	0.005 (0.008)
Constant	-11.326*** (0.175)
Observations	2,661,435
Log Likelihood	-56,045.610
Akaike Inf. Crit.	112,123.200
Bayesian Inf. Crit.	112,327.900
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 34: Episodic
countryEU	-0.147*** (0.007)
countryGB	-0.204*** (0.004)
has_hashtag1	0.017*** (0.005)
has Mention1	0.174*** (0.005)
has_url1	0.451*** (0.005)
isQuote_status1	-0.866*** (0.005)
is_reply1	-1.078*** (0.005)
is_verified1	0.578*** (0.011)
log_chars	-0.288*** (0.004)
log_followers	-0.006*** (0.001)
log_following	0.024*** (0.001)
log statuses	0.043*** (0.001)
Constant	1.857*** (0.032)
Observations	2,661,435
Log Likelihood	-1,633,108.000
Akaike Inf. Crit.	3,266,249.000
Bayesian Inf. Crit.	3,266,453.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 35: Thematic
countryEU	-0.249*** (0.008)
countryGB	-0.012*** (0.005)
has_hashtag1	-0.273*** (0.005)
has Mention1	-0.062*** (0.004)
has_url1	-0.471*** (0.005)
isQuote_status1	1.094*** (0.005)
is_reply1	1.061*** (0.005)
is_verified1	-0.408*** (0.009)
log_chars	1.845*** (0.004)
log_followers	-0.047*** (0.001)
log_following	0.022*** (0.001)
log statuses	-0.018*** (0.001)
Constant	-9.106*** (0.036)
Observations	2,661,435
Log Likelihood	-1,489,756.000
Akaike Inf. Crit.	2,979,544.000
Bayesian Inf. Crit.	2,979,749.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
E Frame-building (ideology) regressions
Tables 36-62 show independent variable coefficients for logit regressions predicting frames from ideology.
Table 36: Capacity.and-resources
has_hastag1	-0.268*** (0.014)
has Mention1	-0.056*** (0.011)
has_url1	-0.049*** (0.013)
is quote_status1	0.248*** (0.012)
is_reply1	0.329*** (0.011)
is_verified1	-0.084*** (0.025)
log_chars	0.767*** (0.010)
log_followers	-0.013*** (0.004)
log_following	-0.019*** (0.004)
log statuses	-0.023*** (0.003)
ideology	0.178*** (0.002)
Constant	-6.763*** (0.101)
Observations	1,680,164
Log Likelihood	-373,804.500
Akaike Inf. Crit.	747,638.900
Bayesian Inf. Crit.	747,823.900
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 37: Crime.and.Punishment
has_hastag1	-0.074*** (0.006)
has Mention1	-0.145*** (0.005)
has_url1	0.152*** (0.006)
is quote_status1	0.009 (0.006)
is_reply1	0.096*** (0.006)
is_verified1	-0.213*** (0.011)
log_chars	0.302*** (0.005)
log_followers	-0.010*** (0.002)
log_following	0.010*** (0.002)
log statuses	0.021*** (0.001)
ideology	0.174*** (0.001)
Constant	-2.652*** (0.042)
Observations	1,680,164
Log Likelihood	-1,052,324.000
Akaike Inf. Crit.	2,104,679.000
Bayesian Inf. Crit.	2,104,864.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 38: Cultural.Identity
has_hastag1	-0.104*** (0.008)
has Mention1	-0.336*** (0.008)
has_url1	-0.311*** (0.009)
isQuote_status1	0.022*** (0.008)
isreply1	0.253*** (0.008)
is_verified1	-0.043*** (0.014)
log_chars	0.725*** (0.007)
log_followers	0.025*** (0.002)
log_following	-0.005** (0.003)
log statuses	-0.021*** (0.002)
ideology	-0.097*** (0.001)
Constant	-4.993*** (0.051)
Observations	1,680,164
Log Likelihood	-654,480.300
Akaike Inf. Crit.	1,308,991.000
Bayesian Inf. Crit.	1,309,176.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 39: Economic
has_hastag1	-0.140*** (0.007)
has Mention1	-0.003 (0.006)
has_url1	-0.067*** (0.008)
isQuote_status1	0.181*** (0.006)
is_reply1	0.138*** (0.006)
is_verified1	-0.043*** (0.013)
log_chars	0.973*** (0.006)
log_followers	-0.069*** (0.002)
log_following	0.025*** (0.002)
log statuses	0.041*** (0.002)
ideology	0.048*** (0.001)
Constant	-6.375*** (0.066)
Observations	1,680,164
Log Likelihood	-882,709.100
Akaike Inf. Crit.	1,765,448.000
Bayesian Inf. Crit.	1,765,633.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 42: Health.and.Safety
has_hastag1	-0.056*** (0.007)
has Mention1	-0.174*** (0.006)
has_url1	0.500*** (0.008)
isQuote_status1	-0.180*** (0.007)
is_reply1	-0.118*** (0.006)
is_verified1	-0.123*** (0.013)
log_chars	0.429*** (0.006)
log_followers	-0.013*** (0.002)
log_following	0.025*** (0.002)
log statuses	0.022*** (0.002)
ideology	0.027*** (0.001)
Constant	-4.194*** (0.086)
Observations	1,680,164
Log Likelihood	-814,400.700
Akaike Inf. Crit.	1,628,831.000
Bayesian Inf. Crit.	1,629,016.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 40: External.Regulation.and.Reputation
has_hastag1	0.097*** (0.014)
has Mention1	-0.082*** (0.013)
has_url1	0.634*** (0.020)
isQuote_status1	-0.100*** (0.014)
is_reply1	-0.082*** (0.013)
is_verified1	-0.068** (0.027)
log_chars	0.586*** (0.012)
log_followers	0.004 (0.004)
log_following	-0.031*** (0.005)
log statuses	0.035*** (0.003)
ideology	0.067*** (0.003)
Constant	-7.099*** (0.092)
Observations	1,680,164
Log Likelihood	-254,086.900
Akaike Inf. Crit.	508,203.700
Bayesian Inf. Crit.	508,388.700
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 43: Legality..Constitutionality..Jurisdiction
has_hastag1	-0.046*** (0.008)
has Mention1	0.011 (0.007)
has_url1	0.185*** (0.010)
isQuote_status1	-0.221*** (0.008)
is_reply1	-0.229*** (0.007)
is_verified1	0.345*** (0.014)
log_chars	0.799*** (0.007)
log_followers	-0.060*** (0.002)
log_following	0.022*** (0.003)
log statuses	0.077*** (0.002)
ideology	-0.043*** (0.001)
Constant	-6.462*** (0.052)
Observations	1,680,164
Log Likelihood	-652,442.400
Akaike Inf. Crit.	1,304,915.000
Bayesian Inf. Crit.	1,305,100.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 41: Fairness.and.Equality
has_hastag1	0.065*** (0.009)
has Mention1	-0.126*** (0.008)
has_url1	-0.195*** (0.010)
isQuote_status1	0.564*** (0.008)
is_reply1	0.562*** (0.008)
is_verified1	-0.215*** (0.016)
log_chars	0.909*** (0.007)
log_followers	0.008*** (0.003)
log_following	0.001 (0.003)
log statuses	-0.021*** (0.002)
ideology	-0.169*** (0.001)
Constant	-6.508*** (0.050)
Observations	1,680,164
Log Likelihood	-615,207.800
Akaike Inf. Crit.	1,230,446.000
Bayesian Inf. Crit.	1,230,631.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 44: Morality.and.Ethics
has_hastag1	0.186*** (0.009)
has Mention1	-0.077*** (0.008)
has_url1	-0.013 (0.012)
is quote_status1	0.257*** (0.009)
is_reply1	-0.058*** (0.009)
is_verified1	-0.214*** (0.016)
log_chars	0.905*** (0.008)
log_followers	0.013*** (0.003)
log_following	0.018*** (0.003)
log statuses	-0.034*** (0.002)
ideology	-0.411*** (0.002)
Constant	-6.804*** (0.082)
Observations	1,680,164
Log Likelihood	-478,969.600
Akaike Inf. Crit.	957,969.100
Bayesian Inf. Crit.	958,154.100
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 45: Policy.Prescription.and.Evaluation
has_hastag1	0.223*** (0.006)
has Mention1	0.086*** (0.005)
has_url1	0.126*** (0.007)
is之势 status1	-0.001 (0.006)
isreply1	-0.162*** (0.006)
is_verified1	0.336*** (0.011)
log_chars	0.730*** (0.005)
log_followers	-0.038*** (0.002)
log_following	-0.011*** (0.002)
log statuses	0.039*** (0.001)
ideology	0.037*** (0.001)
Constant	-4.844*** (0.037)
Observations	1,680,164
Log Likelihood	-1,001,011.000
Akaike Inf. Crit.	2,002,052.000
Bayesian Inf. Crit.	2,002,237.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 48: Quality.of.Life
has_hastag1	-0.159*** (0.015)
has Mention1	-0.452*** (0.013)
has_url1	0.122*** (0.018)
isQuote_status1	0.184*** (0.013)
is_reply1	0.366*** (0.013)
is_verified1	0.046** (0.022)
log_chars	1.071*** (0.012)
log_followers	0.069*** (0.004)
log_following	-0.039*** (0.004)
log statuses	-0.100*** (0.003)
ideology	-0.103*** (0.002)
Constant	-7.934*** (0.070)
Observations	1,680,164
Log Likelihood	-287,794.400
Akaike Inf. Crit.	575,618.700
Bayesian Inf. Crit.	575,803.700
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 46: Political.Factors.and.Implications
has_hastag1	0.267*** (0.006)
has Mention1	0.101*** (0.005)
has_url1	0.152*** (0.006)
isQuote_status1	0.113*** (0.006)
is_reply1	-0.333*** (0.005)
is_verified1	-0.186*** (0.010)
log_chars	1.063*** (0.005)
log_followers	-0.010*** (0.002)
log_following	-0.009*** (0.002)
log statuses	0.064*** (0.001)
ideology	0.066*** (0.001)
Constant	-6.140*** (0.034)
Observations	1,680,164
Log Likelihood	-1,097,548.000
Akaike Inf. Crit.	2,195,126.000
Bayesian Inf. Crit.	2,195,311.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 49: Security.and Defense
has_hastag1	0.306*** (0.007)
has Mention1	-0.075*** (0.006)
has_url1	0.254*** (0.008)
isQuote_status1	-0.075*** (0.006)
is_reply1	-0.142*** (0.006)
is_verified1	-0.043*** (0.013)
log_chars	0.697*** (0.006)
log_followers	-0.013*** (0.002)
log_following	-0.014*** (0.002)
log statuses	0.023*** (0.002)
ideology	0.177*** (0.001)
Constant	-5.359*** (0.080)
Observations	1,680,164
Log Likelihood	-859,551.100
Akaike Inf. Crit.	1,719,132.000
Bayesian Inf. Crit.	1,719,317.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 47: Public.Sentiment
has_hastag1	0.368*** (0.011)
has Mention1	-0.030*** (0.010)
has_url1	0.383*** (0.016)
isQuote_status1	-0.142*** (0.012)
is_reply1	-0.308*** (0.011)
is_verified1	-0.065*** (0.021)
log_chars	0.581*** (0.010)
log_followers	0.047*** (0.004)
log_following	-0.020*** (0.004)
log statuses	-0.018*** (0.003)
ideology	-0.060*** (0.002)
Constant	-6.130*** (0.088)
Observations	1,680,164
Log Likelihood	-332,620.700
Akaike Inf. Crit.	665,271.500
Bayesian Inf. Crit.	665,456.500
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 50: Threat..Fiscal
has_hastag1	-0.157*** (0.012)
has Mention1	-0.0002 (0.011)
has_url1	-0.279*** (0.011)
is quote_status1	0.586*** (0.010)
is_reply1	0.573*** (0.011)
is_verified1	-1.036*** (0.039)
log_chars	0.576*** (0.009)
log_followers	-0.037*** (0.004)
log_following	0.021*** (0.004)
log statuses	-0.037*** (0.002)
ideology	0.505*** (0.002)
Constant	-5.913*** (0.098)
Observations	1,680,164
Log Likelihood	-440,199.100
Akaike Inf. Crit.	880,428.300
Bayesian Inf. Crit.	880,613.300
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 51: Threat..Jobs
has_hastag1	-0.061* (0.035)
has Mention1	-0.170*** (0.031)
has_url1	-0.220*** (0.033)
isQuote_status1	0.465*** (0.031)
is_reply1	0.693*** (0.032)
is_verified1	-0.649*** (0.091)
log_chars	0.610*** (0.026)
log_followers	-0.097*** (0.010)
log_following	-0.011 (0.011)
log statuses	0.037*** (0.007)
ideology	0.094*** (0.005)
Constant	-7.864*** (0.136)
Observations	1,680,164
Log Likelihood	-80,905.320
Akaike Inf. Crit.	161,840.600
Bayesian Inf. Crit.	162,025.700
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 54: Victim..Discrimination
has_hastag1	-0.199*** (0.011)
has Mention1	0.180*** (0.009)
has_url1	-0.213*** (0.013)
isQuote_status1	0.232*** (0.010)
is_reply1	-0.003 (0.009)
is_verified1	0.300*** (0.018)
log_chars	1.120*** (0.009)
log_followers	-0.151*** (0.003)
log_following	0.124*** (0.004)
log statuses	0.111*** (0.002)
ideology	-0.485*** (0.002)
Constant	-8.942*** (0.072)
Observations	1,680,164
Log Likelihood	-417,485.600
Akaike Inf. Crit.	835,001.200
Bayesian Inf. Crit.	835,186.200
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 52: Threat..National.Cohesion
has_hastag1	0.270*** (0.011)
has Mention1	-0.139*** (0.011)
has_url1	-0.451*** (0.012)
isQuote_status1	0.756*** (0.011)
is_reply1	0.634*** (0.012)
is_verified1	-1.171*** (0.043)
log_chars	0.806*** (0.010)
log_followers	-0.016*** (0.004)
log_following	0.017*** (0.004)
log statuses	-0.009*** (0.003)
ideology	0.479*** (0.002)
Constant	-7.435*** (0.066)
Observations	1,680,164
Log Likelihood	-382,405.800
Akaike Inf. Crit.	764,841.500
Bayesian Inf. Crit.	765,026.600
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 55: Victim..Global.Economy
has_hastag1	-0.387*** (0.051)
has Mention1	-0.037 (0.039)
has_url1	0.033 (0.051)
isQuote_status1	-0.078* (0.044)
is_reply1	0.156*** (0.039)
is_verified1	0.445*** (0.071)
log_chars	0.876*** (0.035)
log_followers	-0.065*** (0.012)
log_following	0.006 (0.014)
log statuses	-0.024*** (0.009)
ideology	-0.053*** (0.007)
Constant	-9.659*** (0.194)
Observations	1,680,164
Log Likelihood	-47,175.170
Akaike Inf. Crit.	94,380.340
Bayesian Inf. Crit.	94,565.350
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 53: Threat..Public.Order
has_hastag1	0.190*** (0.007)
has Mention1	-0.012** (0.006)
has_url1	-0.005 (0.007)
isQuote_status1	0.314*** (0.006)
is_reply1	0.258*** (0.006)
is_verified1	-0.666*** (0.016)
log_chars	0.421*** (0.005)
log_followers	-0.042*** (0.002)
log_following	0.035*** (0.002)
log statuses	-0.005*** (0.001)
ideology	0.506*** (0.001)
Constant	-3.815*** (0.054)
Observations	1,680,164
Log Likelihood	-902,962.200
Akaike Inf. Crit.	1,805,954.000
Bayesian Inf. Crit.	1,806,139.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 56: Victim..Humanitarian
has_hastag1	0.184*** (0.009)
has Mention1	-0.168*** (0.008)
has_url1	0.460*** (0.013)
isQuote_status1	-0.177*** (0.010)
is_reply1	-0.506*** (0.009)
is_verified1	0.188*** (0.015)
log_chars	0.491*** (0.008)
log_followers	0.005 (0.003)
log_following	0.035*** (0.003)
log statuses	0.021*** (0.002)
ideology	-0.603*** (0.002)
Constant	-5.537*** (0.103)
Observations	1,680,164
Log Likelihood	-409,562.800
Akaike Inf. Crit.	819,155.600
Bayesian Inf. Crit.	819,340.600
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 57: Victim..War
has_hastag1	-0.067 (0.052)
has Mention1	-0.468*** (0.045)
has_url1	0.441*** (0.078)
isQuote_status1	-0.116** (0.050)
is_reply1	0.173*** (0.047)
is_verified1	0.379*** (0.074)
log_chars	1.010*** (0.044)
log_followers	-0.021 (0.014)
log_following	0.0003 (0.016)
log statuses	-0.004 (0.011)
ideology	-0.465*** (0.010)
Constant	-11.222*** (0.240)
Observations	1,680,164
Log Likelihood	-31,227.890
Akaike Inf. Crit.	62,485.790
Bayesian Inf. Crit.	62,670.810
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 60: Hero..Worker
has_hastag1	-0.246*** (0.031)
has Mention1	-0.092*** (0.025)
has_url1	-0.027 (0.029)
isQuote_status1	0.166*** (0.028)
is_reply1	0.600*** (0.026)
is_verified1	0.091** (0.046)
log_chars	0.348*** (0.022)
log_followers	-0.016** (0.008)
log_following	-0.004 (0.009)
log statuses	-0.048*** (0.006)
ideology	-0.322*** (0.005)
Constant	-5.766*** (0.136)
Observations	1,680,164
Log Likelihood	-103,008.500
Akaike Inf. Crit.	206,047.000
Bayesian Inf. Crit.	206,232.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 58: Hero..Cultural.Diversity
has_hastag1	0.209*** (0.026)
has Mention1	-0.067*** (0.025)
has_url1	-0.562*** (0.029)
isQuote_status1	0.448*** (0.025)
is_reply1	0.343*** (0.026)
is_verified1	0.184*** (0.043)
log_chars	0.431*** (0.023)
log_followers	0.040*** (0.008)
log_following	0.001 (0.009)
log statuses	-0.133*** (0.006)
ideology	-0.533*** (0.006)
Constant	-5.399*** (0.141)
Observations	1,680,164
Log Likelihood	-89,983.880
Akaike Inf. Crit.	179,997.800
Bayesian Inf. Crit.	180,182.800
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 61: Episodic
has_hastag1	0.038*** (0.007)
has Mention1	0.263*** (0.006)
has_url1	0.560*** (0.006)
is quote_status1	-0.969*** (0.006)
is_reply1	-1.188*** (0.006)
is_verified1	0.395*** (0.014)
log_chars	-0.369*** (0.005)
log_followers	0.018*** (0.002)
log_following	0.024*** (0.002)
log statuses	0.033*** (0.001)
ideology	-0.171*** (0.001)
Constant	2.346*** (0.040)
Observations	1,680,164
Log Likelihood	-988,528.600
Akaike Inf. Crit.	1,977,087.000
Bayesian Inf. Crit.	1,977,272.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 59: Hero..Integration
has_hastag1	-0.076*** (0.020)
has Mention1	-0.244*** (0.017)
has_url1	-0.158*** (0.022)
isQuote_status1	0.188*** (0.018)
is_reply1	0.235*** (0.018)
is_verified1	0.205*** (0.029)
log_chars	0.636*** (0.016)
log_followers	0.069*** (0.005)
log_following	-0.036*** (0.006)
log statuses	-0.122*** (0.004)
ideology	-0.297*** (0.003)
Constant	-5.862*** (0.093)
Observations	1,680,164
Log Likelihood	-166,396.500
Akaike Inf. Crit.	332,823.000
Bayesian Inf. Crit.	333,008.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
Table 62: Thematic
has_hastag1	-0.170*** (0.006)
has Mention1	-0.164*** (0.006)
has_url1	-0.579*** (0.006)
is quote_status1	1.069*** (0.006)
is_reply1	1.068*** (0.006)
is_verified1	-0.406*** (0.011)
log_chars	2.002*** (0.006)
log_followers	-0.013*** (0.002)
log_following	-0.036*** (0.002)
log statuses	-0.045*** (0.001)
ideology	0.205*** (0.001)
Constant	-9.476*** (0.042)
Observations	1,680,164
Log Likelihood	-914,986.900
Akaike Inf. Crit.	1,830,004.000
Bayesian Inf. Crit.	1,830,189.000
Note:  ${}^{ * }\mathrm{p} < {0.1};{}^{* * }\mathrm{p} < {0.05};{}^{* *  * }\mathrm{p} < {0.01}$
F Frame-setting (audience response) regressions
Tables 63-67 show independent variable coefficients for linear regressions predicting favorite and retweet counts from frames. Results from Table 63 are discussed in the main paper. We find comparable effects of frames on audience responses when excluding frames from the regression model with F1 scores below 0.5 (Figure 64), and when fitting separate regressions for each frame type (Figures 65-67).
Table 63: Fit audience response variables on all frames
log_f favorites	log_retweets
Capacity.and.Resource1	-0.017** (0.004)	-0.010*** (0.003)
Crime.and.Punishment1	-0.018*** (0.002)	0.018*** (0.002)
Cultural.Identity1	0.020 (0.003)	0.001 (0.002)
Economic1	0.010*** (0.002)	0.017*** (0.002)
Episodic1	0.002*** (0.002)	0.013*** (0.002)
External.Regulation.and.Reputation1	-0.020 (0.004)	-0.001 (0.003)
Fairness.and.Equality1	0.032*** (0.003)	0.021*** (0.002)
Health.and.Safety1	-0.007*** (0.002)	0.017*** (0.002)
Hero..Cultural.Diversity1	0.043 (0.008)	-0.011 (0.006)
Hero..Integration1	0.100*** (0.005)	0.019*** (0.004)
Hero..Worker1	-0.017 (0.007)	0.005 (0.006)
Legality..Constitutionality..Jurisdiction1	0.002*** (0.002)	0.020*** (0.002)
Morality.and.Ethics1	0.066*** (0.003)	0.022*** (0.002)
Policy.Prescription.and.Evaluation1	-0.003* (0.002)	0.004*** (0.001)
Political.Factors.and.Implications1	0.008*** (0.002)	0.031*** (0.001)
Public.Sentiment1	0.030*** (0.004)	0.023*** (0.003)
Quality.of-Life1	0.018 (0.004)	-0.004 (0.003)
Security.and.Defense1	-0.017*** (0.002)	0.013*** (0.002)
Thematic1	0.007*** (0.002)	0.014*** (0.002)
Threat..Fiscal1	-0.016*** (0.003)	0.011*** (0.003)
Threat..Jobs1	0.019*** (0.009)	0.027*** (0.007)
Threat..National.Cohesion1	-0.016*** (0.003)	0.013*** (0.003)
Threat..Public.Order1	0.020*** (0.002)	0.028*** (0.002)
Victim..Discrimination1	0.048*** (0.004)	0.029*** (0.003)
Victim..Global.Economy1	-0.033 (0.012)	-0.014 (0.010)
Victim..Humanitarian1	0.008*** (0.003)	0.064*** (0.003)
Victim..War1	0.013 (0.014)	0.011 (0.012)
has_hashtag1	-0.048*** (0.003)	-0.020*** (0.002)
hasmention1	-0.116*** (0.002)	-0.096*** (0.002)
has_url1	-0.299*** (0.003)	-0.168*** (0.002)
is quote_status1	-0.010*** (0.003)	-0.071*** (0.002)
is_reply1	0.050*** (0.003)	-0.129*** (0.002)
is_verified1	0.666*** (0.005)	0.590*** (0.004)
log_chars	0.326*** (0.002)	0.220*** (0.002)
log_followers	0.318*** (0.001)	0.243*** (0.001)
log_following	-0.123*** (0.001)	-0.087*** (0.001)
log statuses	-0.145*** (0.001)	-0.098*** (0.001)
ideology	-0.046*** (0.001)	-0.007*** (0.0004)
Constant	-0.747*** (0.033)	-0.739*** (0.012)
Observations	1,262,326	1,262,326
Log Likelihood	-1,613,009.000	-1,335,368.000
Akaike Inf. Crit.	3,226,105.000	2,670,822.000
Bayesian Inf. Crit.	3,226,623.000	2,671,340.000
$^{*}\mathrm{p} <   0.05$ $^{**}\mathrm{p} <   0.01$ $^{**}\mathrm{p} <   0.005$