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会话级语法相似度度量。

Conversation level syntax similarity metric.

机构信息

Department of Computer Science, University of Southern California, 3620 S. McClintock Ave, Los Angeles, CA, 90089-1061, USA.

Department of Psychology, University of Southern California, 3620 S. McClintock Ave, Los Angeles, CA, 90089-1061, USA.

出版信息

Behav Res Methods. 2018 Jun;50(3):1055-1073. doi: 10.3758/s13428-017-0926-2.

DOI:10.3758/s13428-017-0926-2
PMID:28699124
Abstract

The syntax and semantics of human language can illuminate many individual psychological differences and important dimensions of social interaction. Accordingly, psychological and psycholinguistic research has begun incorporating sophisticated representations of semantic content to better understand the connection between word choice and psychological processes. In this work we introduce ConversAtion level Syntax SImilarity Metric (CASSIM), a novel method for calculating conversation-level syntax similarity. CASSIM estimates the syntax similarity between conversations by automatically generating syntactical representations of the sentences in conversation, estimating the structural differences between them, and calculating an optimized estimate of the conversation-level syntax similarity. After introducing and explaining this method, we report results from two method validation experiments (Study 1) and conduct a series of analyses with CASSIM to investigate syntax accommodation in social media discourse (Study 2). We run the same experiments using two well-known existing syntactic metrics, LSM and Coh-Metrix, and compare their results to CASSIM. Overall, our results indicate that CASSIM is able to reliably measure syntax similarity and to provide robust evidence of syntax accommodation within social media discourse.

摘要

人类语言的语法和语义可以阐明许多个体心理差异和社会互动的重要维度。因此,心理和心理语言学研究已经开始纳入语义内容的复杂表示形式,以更好地理解词汇选择与心理过程之间的联系。在这项工作中,我们引入了会话级语法相似性度量(CASSIM),这是一种计算会话级语法相似性的新方法。CASSIM 通过自动生成会话中句子的语法表示形式来估计会话之间的语法相似性,估计它们之间的结构差异,并计算会话级语法相似性的优化估计值。在介绍和解释了这种方法之后,我们报告了两项方法验证实验(研究 1)的结果,并使用 CASSIM 进行了一系列分析,以研究社交媒体话语中的语法顺应(研究 2)。我们使用两种著名的现有语法度量标准 LSM 和 Coh-Metrix 运行了相同的实验,并将它们的结果与 CASSIM 进行了比较。总体而言,我们的结果表明,CASSIM 能够可靠地测量语法相似性,并为社交媒体话语中的语法顺应提供有力证据。

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