Analyzing Corpus-Derived Lexico-Grammatical Patterns Including Lexical Choices Modality Transitivity and Evaluative Language in Online News Portals and Social Media News Discourse to Identify Ideological Positioning Using a Corpus-Assisted Discourse Appro

Abstract

The paper discusses the application of corpus-based lexico-grammatical patterns as ideological positioning signs in online news portals and news discussion platforms in social media by applying a corpus-based discourse analysis method. The study aims at examining the role that the lexical choices, modality, transitivity, and evaluative language play in the development of ideology in digital news platforms. The study has been anchored on the theoretical basis of Critical Discourse Analysis, Systematic Functional Linguistics, and Appraisal Theory, which gives an analytical privilege in the study of language, power and evaluation in news discourse. In methodology, the research assumes a qualitative-dominant, mixed-method study design in the context of a corpus-assisted discourse studies design. There were two similar corpora, an online news corpus and a social media news corpus. Purposive and stratified sampling was used to collect data out of existing digital news portals and social media accounts of verified news organizations. AntConc was utilized to provide corpus analysis to capture frequency patterns, keys, collocations, and concordance line, and then subjective interpretation of discourses took place. The results indicate obvious ideological differences on a platform basis. Construction of ideology in online news portals is based on institutional framing, epistemic hedging, passive transitivity, restrained evaluation, and social media news discourse is based on people-centered lexical choices, deontic modality, explicit agency, and affective evaluation. The paper reveals the usefulness of corpus-based discourse analysis in revealing implicit ideological messages of modern digital news discourse.