早先的欧洲把所有的果实都称为 apple,这或许是圣经里有关人类祖先亚当和夏娃在伊甸园偷食禁果的故事影响所致。现代英语中的 pineapple(菠萝)一词实质上是 the apple of pine 的变体。love apple 意思是蕃茄,西红柿。法语中与英语词 ap...早先的欧洲把所有的果实都称为 apple,这或许是圣经里有关人类祖先亚当和夏娃在伊甸园偷食禁果的故事影响所致。现代英语中的 pineapple(菠萝)一词实质上是 the apple of pine 的变体。love apple 意思是蕃茄,西红柿。法语中与英语词 apple 相对应的词是 pomme,也有 pomme de terre(=英语词potato 土豆),pomme d’amour(=英语词 tomato,love apple(西红柿)等词。它们部与 apple 有关。翻开英文辞典,我们就会发现 apple 一词有两义:一曰“苹果’:一曰“类似苹果的各种果实”。我们知道桔子 orange 是桔黄色的,似金黄,在拉丁语中它称之为 aurangia,意为 golden apple。orange 原有的起首字母是 n,在法语和拉丁语里把 n 丢掉时,在梵语里仍然有之,为 norange。展开更多
The study use crawler to get 842,917 hot tweets written in English with keyword Chinese or China. Topic modeling and sentiment analysis are used to explore the tweets. Thirty topics are extracted. Overall, 33% of the ...The study use crawler to get 842,917 hot tweets written in English with keyword Chinese or China. Topic modeling and sentiment analysis are used to explore the tweets. Thirty topics are extracted. Overall, 33% of the tweets relate to politics, and 20% relate to economy, 21% relate to culture, and 26% relate to society. Regarding the polarity, 55% of the tweets are positive, 31% are negative and the other 14% are neutral. There are only 25.3% of the tweets with obvious sentiment, most of them are joy.展开更多
文摘早先的欧洲把所有的果实都称为 apple,这或许是圣经里有关人类祖先亚当和夏娃在伊甸园偷食禁果的故事影响所致。现代英语中的 pineapple(菠萝)一词实质上是 the apple of pine 的变体。love apple 意思是蕃茄,西红柿。法语中与英语词 apple 相对应的词是 pomme,也有 pomme de terre(=英语词potato 土豆),pomme d’amour(=英语词 tomato,love apple(西红柿)等词。它们部与 apple 有关。翻开英文辞典,我们就会发现 apple 一词有两义:一曰“苹果’:一曰“类似苹果的各种果实”。我们知道桔子 orange 是桔黄色的,似金黄,在拉丁语中它称之为 aurangia,意为 golden apple。orange 原有的起首字母是 n,在法语和拉丁语里把 n 丢掉时,在梵语里仍然有之,为 norange。
文摘The study use crawler to get 842,917 hot tweets written in English with keyword Chinese or China. Topic modeling and sentiment analysis are used to explore the tweets. Thirty topics are extracted. Overall, 33% of the tweets relate to politics, and 20% relate to economy, 21% relate to culture, and 26% relate to society. Regarding the polarity, 55% of the tweets are positive, 31% are negative and the other 14% are neutral. There are only 25.3% of the tweets with obvious sentiment, most of them are joy.