Trnavac, Radoslava, & Taboada, Maite. (2020). Positive Appraisal in Online News Comments. In Kerry Mullan, Bert Peeters, & Lauren Sadow (Eds.), Studies in ethnopragmatics, cultural semantics, and intercultural communication: Vol. 1. Ethnopragmatics and semantic analysis (pp. 185–206). Singapore: Springer.
DOI: https://doi.org/10.1007/978-981-32-9983-2_10
Abstract
This chapter investigates the linguistic expression of positive evaluation in English and describes a preliminary typology of linguistic devices used for positive evaluation. Using corpus-assisted analysis, we classify some of the resources that play a role in the expression of positive evaluation into phenomena in the lexicogrammar and phenomena that belong in discourse semantics and compare those resources to the ones deployed for negative evaluation (see the work on negative evaluation in Taboada et al. in Corpus Pragmat, 1:57–76, 2017). This general classification of evaluative devices overlaps with the planes of expression in systemic functional linguistics. Our data comes from a collection of opinion articles and the comments associated with them (Kolhatkar et al., in the SFU Opinion and Comments Corpus: A corpus for the analysis of online news comments, under review). We use a set of 1000 comments previously annotated for Appraisal (Martin and White in The language of evaluation. Palgrave, New York, 2005), including labels of Attitude (Affect, Judgement, Appreciation) and polarity (positive, negative, neutral). The central component of the chapter is the analysis of the resources used by commenters to express positive evaluation. We explore whether they make use of rhetorical figures, following up on our work with Cliff Goddard on the use of rhetorical figures in the expression of negative evaluation (Taboada et al. in Corpus Pragmat, 1:57–76, 2017). We then analyse the semantics of evaluative adjectives using the natural semantic metalanguage approach and follow our previous work on templates that capture different types of adjectives and fall into five groups (Goddard et al., in Funct Lang 26, 2019). Although our corpus analysis is limited, and it includes only a specific type of data (online news comments), the phenomena that we discuss are present across different genres of texts. While our previous work has focused on how to express negative evaluation, this chapter seeks to honour Cliff Goddard and his positive influence by studying how positivity is realized in language.
Research carried out by one or more experienced NSM practitioners
