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Thematic and Microstructure Analysis of Twitter Tweets: A Corpus-Based CDA Study

Abstract

This corpus-based research proposes critical discourse analysis based on Van Dijk’s model in the text of social media. The researcher utilized a mixed method approach that found critical discourse analysis of the Twitter hashtag #we are all Pakistani on Twitter concerning the death exploration of Pakistani senior journalist Arshad Sharif. In textual analysis, based on the theoretical framework Van Dijk's model is divided into three levels microstructure, macrostructure, and Superstructure. Analyzing the Tweets, the researcher applies the microstructure in semantic, lexical, syntactical, and thematical dimensions. For data collection, a corpus of two hundred #hashtag tweets was collected randomly and the fifty most effective tweets were selected for better results interpretations. Corpus-based tweets data tagged through POC CLAWS tagger. AntConc software 3.4.4w (Laurence Anthony) is used for the analysis of semantics, syntactical, and lexical bundles. Eventually, the result shows how the language is utilized in the text to convey meanings as well as text information. It concludes that the most common language in tweets is nouns that represent people, places, things, and ideas. Lexical words are used to refer to previous information and to create unity in speech. Thematic elements in the analysis include loss, respect, death, history, injustice, grief, perseverance, public display, and the response to Arshad Sharif's death. Findings provide a better understanding of how language is used on Twitter to communicate and convey thoughts and feelings about important events. Future research may explore methods, a social cognitive approach that considers macrostructure and superstructure analysis of human rights paradigms.

Keywords

Semantic, Lexical, Microstructure, Syntactic, Tweets

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