Table 6 Results of the validation analysis for the estimated ratings of Chinese words by Word2vec.
From: A large dataset of semantic ratings and its computational extension
Study1 | Dimension1 | Study2 | Dimension2 | df | r |
|---|---|---|---|---|---|
Word2vec (Chinese) | Vision | Binder et al.1 (English) | Vision | 517 | 0.700 |
Word2vec (Chinese) | Vision | Liu et al.22 (Chinese) | Imageability | 1323 | 0.511 |
Word2vec (Chinese) | Vision | Su et al.52 (Chinese) | Imageability | 6975 | 0.755 |
Word2vec (Chinese) | Motor | Binder et al.1 (English) | Motor_General | 517 | 0.479 |
Word2vec (Chinese) | Motor | Heard et al.45 (English) | Pantomime | 206 | 0.634 |
Word2vec (Chinese) | Socialness | Binder et al.1 (English) | Social | 517 | 0.635 |
Word2vec (Chinese) | Socialness | Diveica et al.3 (English) | Socialness | 2003 | 0.682 |
Word2vec (Chinese) | Emotion | Binder et al.1 (English) | Pleasant_minus_Unpleasant | 517 | 0.741 |
Word2vec (Chinese) | Emotion | Xu et al.55 (Chinese) | Valence | 6087 | 0.828 |
Word2vec (Chinese) | Emotion_abs + 1 | Binder et al.1 (English) | Arousal | 517 | 0.563 |
Word2vec (Chinese) | Emotion_abs + 1 | Tamir et al.5 (English) | Emotion | 159 | 0.607 |
Word2vec (Chinese) | Emotion_abs + 1 | Xu et al.55 (Chinese) | Arousal | 6087 | 0.573 |
Word2vec (Chinese) | Time | Binder et al.1 (English) | Time_General | 517 | 0.603 |
Word2vec (Chinese) | Space | Binder et al.1 (English) | Space_General | 517 | 0.666 |
