Abstract
Our corpus-based, multivariate approach to the analysis of text is keyed to the interaction of two dozen language features that have shown potential for assessing affect, agency, evaluation and intention. They include public and private or perceptual verbs; several categories of adverbs, modals, pronouns and discourse markers. The language features, which we use as variables, make up what text and corpus linguists define as stance. Stance is how people use their words to signal confidence or doubt, appraisal or judgment [1] about topics, values, audiences, situations, or viewpoints. Speakers construct different personae out of the ways they use language features that signal modality, evidentiality, hedging, attribution, concession, or consequentiality.
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References
Biber, D., Finegan, E.: Styles of stance in English: Lexical and grammatical marking of evidentiality and affect. Text 9, 93–125 (1989)
Mason, P., Davis, B., Bosley, D.: Stance analysis: when people talk online. In: Krishnamurthy II, S. (ed.) Innovations in E-Marketing. Idea Group, Hershey (2005) (in press)
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Davis, B., Lord, V., Mason, P. (2005). More Than a Summary: Stance-Shift Analysis. In: Kantor, P., et al. Intelligence and Security Informatics. ISI 2005. Lecture Notes in Computer Science, vol 3495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427995_71
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DOI: https://doi.org/10.1007/11427995_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25999-2
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