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  5. 2012.01.10.remarks_in_manchester_following_the_new_hampshire_primary

Jon Huntsman

This speech titled 2012.01.10.remarks_in_manchester_following_the_new_hampshire_primary originally had 1569 tokens. In its cue-lag representation, it has 42 cue terms and an average lag of 30.9. You can see the original speech or the tokenized/stemmed speech with overlaying cue-lags.

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
Restart ∑Left Center ∑Right
1 __NUM___public 162
✓
0.164 0.123 0.713
✗
0 0 0
2 great_nation 57
✓
0.0143 0.0806 0.372
✗
0.00896 0.0641 0.46
3 call___NUM__ 67
✓
0.0243 0.00637 0.548
✗
0.00219 0.0117 0.407
4 __NUM___trillion 0
✓
0.00398 0 0.00537
✗
0.0287 0.0169 0.945
5 trillion_dollar 0
✓
0.0265 0.000398 0.00657
✗
0.0362 0.0121 0.918
6 nation_secur 11
✓
0.732 0.0569 0.0306
✗
0.0575 0.00975 0.113
7 american_peopl 33
✓
0.403 0.00458 0
✗
0.585 0.00736 0
8 nation_futur 7
✓
0.0255 0.00358 0.00736
✗
0.952 0.0117 0
9 american_peopl 21
✓
0.0822 0.000597 0.000199
✗
0.907 0.0103 0
10 __NUM___centuri 11
✓
0.634 0 0.0464
✗
0.318 0.00119 0.000398
11 american_centuri 68
✓
0.2 0.0167 0.563
✗
0.197 0.000199 0.0235
12 unit_state 82
✓
0.00816 0.000995 0.747
✗
0.00378 0 0.24
13 elect_offici 16
✓
0.0874 0.197 0.1
✗
0.0103 0.00537 0.6
14 problem_solv 31
✓
0.165 0.245 0.114
✗
0.045 0.177 0.254
15 term_limit 41
✓
0.818 0.00279 0.00139
✗
0.156 0.0205 0.00139
16 revolv_door 9
✓
0.0911 0.00139 0.000597
✗
0.892 0.0147 0.000398
17 american_peopl 35
✓
0.255 0.00517 0
✗
0.734 0.00597 0
18 __NUM___year 53
✓
0.303 0.0203 0.00537
✗
0.663 0.00816 0
19 american_peopl 11
✓
0.0655 0.000995 0
✗
0.92 0.0129 0.000199
20 al_qaeda 18
✓
0.539 0.00139 0.0792
✗
0.38 0.000199 0.000199
21 osama_bin_laden 9
✓
0.041 0.00179 0.343
✗
0.534 0.000199 0.08
22 free_elect 9
✓
0.0133 0.00896 0.365
✗
0.226 0.00119 0.386
23 civil_societi 4
✓
0.0139 0.00498 0.0492
✗
0.212 0.00995 0.71
24 troop_home 23
✓
0.0575 0.00517 0.323
✗
0.0488 0.00119 0.565
25 __NUM___mile 90
✓
0.0884 0.0149 0.565
✗
0.00677 0.000199 0.324
26 ten_thousand 6
✓
0.00796 0.00736 0.0438
✗
0.0778 0.0149 0.848
27 thousand_mile 0
✓
0.000597 0.000199 0.00498
✗
0.0844 0.0217 0.888
28 __NUM___mile 24
✓
0.0482 0.00259 0.337
✗
0.0581 0.0127 0.541
29 privat_properti 73
✓
0.451 0.0171 0.205
✗
0.038 0.00139 0.287
30 arm_forc 83
✓
0.0171 0.000398 0.91
✗
0.00398 0 0.0689
31 front_line 30
✓
0.0404 0.00139 0.23
✗
0.00776 0 0.72
32 unit_state 22
✓
0.00139 0.000199 0.219
✗
0.000995 0 0.779
33 same_thing 38
✓
0.00458 0.00438 0.287
✗
0.000199 0 0.704
34 greatest_gener 6
✓
0 0 0.0328
✗
0 0 0.967
35 decad_ago 4
✓
0.000199 0.000398 0.00239
✗
0 0 0.997
36 greatest_gener 16
✓
0 0 0.0109
✗
0 0 0.989
37 earlier_gener 29
✓
0.00756 0.00239 0.0255
✗
0 0 0.965
38 work_hard 45
✓
0.116 0.0613 0.266
✗
0.00239 0.00139 0.553
39 town_hall_meet 59
✓
0.0149 0.0135 0.757
✗
0.00358 0.00557 0.205
40 unit_state 23
✓
0.000995 0.000398 0.248
✗
0.00418 0.000597 0.746
41 town_hall_meet 20
✓
0.0145 0.0183 0.133
✗
0.00418 0.00119 0.829
42 south_carolina 54
✓
0.213 0.102 0.256
✗
0.00796 0.0103 0.41
__END_OF_SPEECH__ 17