Page 190 - Journal of Library Science in China, Vol.47, 2021

ZHANG Wei, WANG Hao, DENG Sanhong & ZHANG Baolong / Sentiment term extraction 189
and application of Chinese ancient poetry text for digital humanities

Other N other N 恼 忄 nao zg N N X N Z E

苦 艹 ku a X Y X Y Z B
Second-class Y knowing U 的 主 白 丶 de zhu uj b X Y Y Y X X N N Z Y O O

Emotion(E) Character classification(T) Phonogram Z 明 日 ming a X Y X X U S

First-class X Pictograph Y 逢 不 辶 一 feng bu zg d N X Y Y X X Y Y Z X O O

Instigate X 而 而 er c X Y X N X O

才 雄 扌 隹 cai xiong d n X N Y Y X X Y N X Z O S
other
N
Morphemes(M) Part of speech tendency of morphemes Part of speech string Surname(N) Low frequency Y 之 仪 丿 亻 zhi yi u ng X N Y N X X Y Y X Z O O

frequency
high
X

秦 张 苏 弓 禾 艹 zhang qin su q nr j N N N Y Y Y X Y X X X X Z U Z O O O

other
Table 1. Induction of Chinese language features based on ancient poetry text
N
Pinyin(P) Character pronunciation component Pinyin string Usual character(U) Second- class Y 有 人 诗 了 月 人 讠 乙 you ren shi le v n n ul X X N Y Y Y Y Y X X X X X X Y N U Y Z Y O O O O

First-class
X

透 露 地 雨 辶 土 lu tou di v v uv N N X Y Y Y X X X N N N Z Z Z E B O
Character font component Radical string Field(F) 婉 女 wan a N Y Y N Z E
other
N
Radical(B) high frequency Y 委 女 wei zg N Y X Y U B

Character feature Description Value Character feature Description Value C B P M E Samples F U N T R