AI Summary & Key Takeaways
AI InsightIn rendering a pragmatic explanation for why certain social media narratives on COVID-19 mis/disinform, the study findings reveal that there are linguistic features in the misinformed and disinformed contents that aid the manipulation of information to give partial information or prevent the eventuality in which the information content can be tagged as a total lie.
📌 3 Key Takeaways
Abstract
The outbreak of Coronavirus 2019, known as COVID-19, has stimulated social unrest in all nations and at the same time has facilitated the spread of mis/ disinformation about the pandemic in both mainstream and new media. It has also stimulated various research works that have investigated mis/disinformation on the pandemic, especially the social media narratives, through various factchecking mechanisms. The fact-checking research that many researchers utilise to authenticate the source of this mis/disinformation about the plague focuses little or no attention on linguistic phenomena in the COVID-19 narratives in the social media discourse. The present paper, which deploys the qualitative method of analysis of information manipulation theory (IMT), investigates the linguistic features of mis/disinformation about COVID-19 from the data drawn from various social media platforms in Nigeria and Iraq. The research findings attempt to answer two research questions: Is mis/disinformation about COVID-19 detectable in the social media discourse pragmatically? Does mis/ disinformation about the pandemic contains any linguistic features which language users utilise to achieve their intended communicative action? The findings, which show that IMT offers a multidimensional approach to the investigation of misinformation and disinformation about COVID-19, indicate that misinformation and disinformation can be detectable from non-observation of Grice's (1989) conversational implicature principles. In rendering a pragmatic explanation for why certain social media narratives on COVID-19 mis/disinform, the study findings reveal that there are linguistic features in the misinformed and disinformed contents that aid the manipulation of information to give partial information or prevent the eventuality in which the information content can be tagged as a total lie.
Özet
The outbreak of Coronavirus 2019, known as COVID-19, has stimulated social unrest in all nations and at the same time has facilitated the spread of mis/ disinformation about the pandemic in both mainstream and new media. It has also stimulated various research works that have investigated mis/disinformation on the pandemic, especially the social media narratives, through various factchecking mechanisms. The fact-checking research that many researchers utilise to authenticate the source of this mis/disinformation about the plague focuses little or no attention on linguistic phenomena in the COVID-19 narratives in the social media discourse. The present paper, which deploys the qualitative method of analysis of information manipulation theory (IMT), investigates the linguistic features of mis/disinformation about COVID-19 from the data drawn from various social media platforms in Nigeria and Iraq. The research findings attempt to answer two research questions: Is mis/disinformation about COVID-19 detectable in the social media discourse pragmatically? Does mis/ disinformation about the pandemic contains any linguistic features which language users utilise to achieve their intended communicative action? The findings, which show that IMT offers a multidimensional approach to the investigation of misinformation and disinformation about COVID-19, indicate that misinformation and disinformation can be detectable from non-observation of Grice's (1989) conversational implicature principles. In rendering a pragmatic explanation for why certain social media narratives on COVID-19 mis/disinform, the study findings reveal that there are linguistic features in the misinformed and disinformed contents that aid the manipulation of information to give partial information or prevent the eventuality in which the information content can be tagged as a total lie.