Table 2.
Summary of regression models analyzed in Study 1
| Google Ngram Corpus | COHA | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Predicting Semantic Stability Between 1800 and 2000 | Predicting Semantic Stability Between 1820 and 2000 | |||||||||||
| Predictors | Estimates | p | Estimates | p | Estimates | p | Estimates | p | Estimates | p | Estimates | p |
| (Intercept) | 0.00 | 1.000 | 0.07 | <0.001 | 0.09 | <0.001 | -0.93 | <0.001 | -0.74 | <0.001 | -1.01 | <0.001 |
| Log Frequency (year 1800/1820) | 0.73 | <0.001 | 0.73 | <0.001 | 0.76 | <0.001 | 0.63 | <0.001 | 0.48 | <0.001 | 0.65 | <0.001 |
| Log Frequency (year 2000) | -0.67 | <0.001 | -0.64 | <0.001 | -0.74 | <0.001 | 0.18 | <0.001 | 0.15 | 0.005 | 0.17 | <0.001 |
| Length | 0.08 | <0.001 | 0.03 | 0.096 | 0.20 | <0.001 | -0.01 | 0.553 | 0.00 | 0.928 | -0.02 | 0.490 |
| Emotionality | -0.01 | 0.437 | 0.01 | 0.748 | -0.01 | 0.466 | -0.01 | 0.686 | 0.00 | 0.969 | 0.00 | 0.838 |
| Valence | 0.04 | <0.001 | 0.05 | 0.004 | 0.04 | 0.007 | -0.00 | 0.842 | 0.01 | 0.699 | 0.01 | 0.624 |
| Arousal | 0.02 | 0.035 | -0.01 | 0.489 | 0.03 | 0.030 | 0.05 | 0.003 | 0.05 | 0.064 | 0.05 | 0.009 |
| Concreteness | 0.09 | <0.001 | 0.01 | 0.518 | 0.11 | <0.001 | 0.08 | <0.001 | 0.11 | <0.001 | 0.07 | 0.002 |
| Log Polysemy | 0.02 | 0.091 | -0.01 | 0.671 | 0.01 | 0.592 | -0.19 | <0.001 | -0.09 | 0.016 | -0.22 | <0.001 |
| Age of Acquisition (AoA) | -0.22 | <0.001 | -0.14 | <0.001 | -0.24 | <0.001 | -0.25 | <0.001 | -0.16 | <0.001 | -0.32 | <0.001 |
| Semantic Processing (RT) | -0.09 | <0.001 | -0.07 | 0.005 | ||||||||
| Lexical Decision (RT) | -0.05 | 0.012 | 0.04 | 0.054 | ||||||||
| Observations | 8133 | 2786 | 4847 | 2845 | 887 | 2046 | ||||||
| R2/R2 | 0.248/0.247 | 0.279/0.276 | 0.255/0.253 | 0.447/0.445 | 0.296/0.288 | 0.477/0.475 | ||||||
Due to constraints of data size, the starting year for the Google Ngram Corpus is 1800 while the starting year for the COHA is 1820. All variables are scaled and mean centered.