论文标题
使用英语Twitter和普通话微博研究跨文化的礼貌
Studying Politeness across Cultures Using English Twitter and Mandarin Weibo
论文作者
论文摘要
跨文化建模礼貌有助于通过发现适当和礼貌的东西来改善跨文化交流。我们研究与美国英语和普通话的礼貌相关的语言特征。首先，我们注释了来自美国的5,300个Twitter帖子和中国的5,300个NINA WEIBO帖子以获得礼貌得分。接下来，我们开发了英语和中文的礼貌功能，“ Politelex”。将其与经过验证的心理语言词典相结合，然后研究语言特征与跨文化的礼貌之间的相关性。我们发现，在普通话中，以未来的对话来对话，与群体的联系认同，而感激之情比在英语Twitter上更有礼貌。与英语Twitter相比，与死亡有关的禁忌话题，代词缺乏或不良的代词选择以及非正式语言与普通话微博的不幸相关。最后，我们构建了基于语言的机器学习模型，以预测普通话的F1分数为0.886，而英语Twitter上的0.774。
Modeling politeness across cultures helps to improve intercultural communication by uncovering what is considered appropriate and polite. We study the linguistic features associated with politeness across US English and Mandarin Chinese. First, we annotate 5,300 Twitter posts from the US and 5,300 Sina Weibo posts from China for politeness scores. Next, we develop an English and Chinese politeness feature set, `PoliteLex'. Combining it with validated psycholinguistic dictionaries, we then study the correlations between linguistic features and perceived politeness across cultures. We find that on Mandarin Weibo, future-focusing conversations, identifying with a group affiliation, and gratitude are considered to be more polite than on English Twitter. Death-related taboo topics, lack of or poor choice of pronouns, and informal language are associated with higher impoliteness on Mandarin Weibo compared to English Twitter. Finally, we build language-based machine learning models to predict politeness with an F1 score of 0.886 on Mandarin Weibo and a 0.774 on English Twitter.
