Measuring Ideological Proportions in Political Speeches

Cue-lag representation

The table below shows the cue-lag representation of the speech. For each cue term, it also displays the posterior distributions over ideology.

#	Cue term	Lag before term	Posterior distribution
#	Cue term	Lag before term	Restart		∑Left	Center	∑Right
1	american_patriot	61		✓	0.985	0.00517	0.00975
1	american_patriot	61		✗	0	0	0
2	pearl_harbor	36		✓	0.125	0	0.000199
2	pearl_harbor	36		✗	0.874	0	0.000398
3	assembl_line	15		✓	0.0746	0	0.00398
3	assembl_line	15		✗	0.921	0	0
4	gi_bill	34		✓	0.106	0	0
4	gi_bill	34		✗	0.894	0	0
5	pearl_harbor	56		✓	0.0993	0	0
5	pearl_harbor	56		✗	0.901	0	0
6	young_men	16		✓	0.0201	0	0
6	young_men	16		✗	0.98	0	0
7	campaign_trail	5		✓	0.0155	0	0.00119
7	campaign_trail	5		✗	0.983	0	0
8	fellow_citizen	191		✓	0.275	0.000199	0.00338
8	fellow_citizen	191		✗	0.722	0	0
9	american_patriot	14		✓	0.0291	0.000199	0.000597
9	american_patriot	14		✗	0.968	0	0.00239
10	same_time	16		✓	0.583	0	0.00836
10	same_time	16		✗	0.409	0	0.000199
11	unit_state	25		✓	0.119	0	0.0165
11	unit_state	25		✗	0.861	0	0.00318
12	fallen_short	89		✓	0.353	0	0
12	fallen_short	89		✗	0.647	0	0
13	cardboard_box	32		✓	0.00338	0	0
13	cardboard_box	32		✗	0.997	0	0
14	street_corner	3		✓	0	0	0
14	street_corner	3		✗	1	0	0
15	long_line	24		✓	0.00239	0.000199	0
15	long_line	24		✗	0.997	0	0
16	pass_law	109		✓	0.0157	0	0
16	pass_law	109		✗	0.984	0	0
17	red_tape	40		✓	0.00358	0	0
17	red_tape	40		✗	0.996	0	0
18	pass_law	31		✓	0.00478	0	0
18	pass_law	31		✗	0.995	0	0
19	famili_member	3		✓	0.000597	0	0.000199
19	famili_member	3		✗	0.999	0	0
20	health_care	1		✓	0.00159	0.000199	0
20	health_care	1		✗	0.998	0	0
21	__NUM___centuri	72		✓	0.043	0	0.000796
21	__NUM___centuri	72		✗	0.956	0	0
22	red_tape	8		✓	0.00199	0	0
22	red_tape	8		✗	0.998	0	0
23	health_care	29		✓	0.00756	0	0.000199
23	health_care	29		✗	0.992	0	0
24	rural_area	10		✓	0.00179	0	0
24	rural_area	10		✗	0.998	0	0
25	support_servic	70		✓	0.00597	0	0
25	support_servic	70		✗	0.994	0	0
26	mental_health	141		✓	0.0199	0	0
26	mental_health	141		✗	0.98	0	0
27	mental_health_profession	11		✓	0.000995	0	0
27	mental_health_profession	11		✗	0.999	0	0
28	north_carolina	123		✓	0.904	0.0318	0.0561
28	north_carolina	123		✗	0.00776	0	0
29	unit_state	89		✓	0.351	0	0.00796
29	unit_state	89		✗	0.639	0	0.00219
30	greatest_gener	18		✓	0.0639	0	0
30	greatest_gener	18		✗	0.936	0	0
31	gi_bill	15		✓	0.0406	0	0
31	gi_bill	15		✗	0.959	0	0
32	strong_support	9		✓	0.0187	0	0
32	strong_support	9		✗	0.981	0	0
33	__NUM___centuri	3		✓	0.116	0	0.000398
33	__NUM___centuri	3		✗	0.884	0	0
34	gi_bill	1		✓	0.0466	0	0
34	gi_bill	1		✗	0.953	0	0
35	jim_webb	8		✓	0.0675	0	0
35	jim_webb	8		✗	0.933	0	0
36	colleg_educ	15		✓	0.271	0	0.000199
36	colleg_educ	15		✗	0.729	0	0
37	medic_center	84		✓	0.268	0	0.0306
37	medic_center	84		✗	0.701	0	0
38	young_men	3		✓	0.00299	0	0
38	young_men	3		✗	0.967	0	0.0299
39	unit_state	49		✓	0.137	0	0.00796
39	unit_state	49		✗	0.853	0	0.00239
40	arm_forc	1		✓	0.00299	0	0.000796
40	arm_forc	1		✗	0.986	0	0.00995
41	full_measur	110		✓	0.0846	0	0.000398
41	full_measur	110		✗	0.915	0	0
42	abraham_lincoln	92		✓	0.13	0.000398	0.00537
42	abraham_lincoln	92		✗	0.864	0	0
43	independ_dai	124		✓	0.241	0.00299	0.112
43	independ_dai	124		✗	0.642	0	0.00239
44	unit_state	22		✓	0.131	0	0.0583
44	unit_state	22		✗	0.73	0	0.0808
	__END_OF_SPEECH__	8

Barack Obama

Cue-lag representation