A Corpus Driven Text Analysis of "Fake Social Media News": A case study of The Indian Chronicles

Abstract

Online media has become a huge strategy for the tremendous extent of information, it spread in all occupations, including publicizing, and news-projecting, and that is only the start. This use of change is a direct result of some novel features, for instance, adaptability, free speech, and insight. Thus, a layperson is always subjected to being exposed to illegitimate “news”. Hence, the need to explore this phenomenon from the textual and linguistic perspective arose. This paper aims to investigate how “fake news” is generated linguistically and which textual features are employed by the “fake news” to make them look legitimate. The data was extracted from the report “The Indian Chronicles” – which is a source of certified counterfeit news. A systemic functional language approach is applied, where for exploration of textual features; a small corpus of fake news is compiled and tagged and through the software UAM, textual features are extracted and identified. Results have displayed, that fake news operates via centralizing participants: inanimate authority material the most, the strategy of manipulation, persuasion was most recurring, and so was foregrounding of inanimate material authority and lastly application of UAM to apply SFL concludes that the socio-cultural perspective of war and hatred in general, is the cause of this generation of fake news.