2016/08/24 by Cliff Goddard, Goddard, Cliff, Maite Taboada +3
Computer Science · Psychology · #Advanced Text Analysis Techniques #Computation and Language (cs.CL) #Emotion and Mood Recognition #FOS: Computer and information sciences #Sentiment Analysis and Opinion Mining
paper · pdf · doi:10.48550/arxiv.1608.06697
openalex publication_date 2016/08/24 · openalex created_date 2016/09/16 · openalex updated_date 2026/07/28
We apply the Natural Semantic Metalanguage (NSM) approach (Goddard and Wierzbicka 2014) to the lexical-semantic analysis of English evaluational adjectives and compare the results with the picture developed in the Appraisal Framework (Martin and White 2005). The analysis is corpus-assisted, with examples mainly drawn from film and book reviews, and supported by collocational and statistical information from WordBanks Online. We propose NSM explications for 24 evaluational adjectives, arguing that they fall into five groups, each of which corresponds to a distinct semantic template. The groups can be sketched as follows: "First-person thought-plus-affect", e.g. wonderful; "Experiential", e.g. entertaining; "Experiential with bodily reaction", e.g. gripping; "Lasting impact", e.g. memorable; "Cognitive evaluation", e.g. complex, excellent. These groupings and semantic templates are compared with the classifications in the Appraisal Framework's system of Appreciation. In addition, we are particularly interested in sentiment analysis, the automatic identification of evaluation and subjectivity in text. We discuss the relevance of the two frameworks for sentiment analysis and other language technology applications.