Automatically Computing Connotative Shifts of Lexical Items

NATURAL LANGUAGE PROCESSING AND INFORMATION SYSTEMS (NLDB 2022)(2022)

引用 0|浏览7
暂无评分
摘要
Connotation is a dimension of lexical meaning at the semantic-pragmatic interface. Connotations can be used to express point of views, perspectives, and implied emotional associations. Variations in connotations of the same lexical item can occur at different level of analysis: from individuals, to community of speech, specific domains, and even time. In this paper, we present a simple yet effective method to assign connotative values to selected target items and to quantify connotation shifts. We test our method via a set of experiments using different social media data (Reddit and Twitter) and languages (English and Italian). While we kept the connotative axis (i.e., the polarity associated to a lexical item) fixed, we investigated connotation shifts along two dimensions: the first target shifts across communities of speech and domain while the second targets shifts in time. Our results indicate the validity of the proposed method and its potential application for the identification of connotation shifts and application to automatically induce specific connotation lexica.
更多
查看译文
关键词
Connotative shift, Word embeddings, Social media
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要