Scrutinizing deceits in fake news using forensic linguistic within French alternative news media
Linguistic instruments together with informatics tools can be used to detect fake news narratives, which are sometimes increasingly difficult to distinguish from true news. This study tries to design the stages of detection of lies in the fake news discourse found in French alternative media using linguistic features. This approach is also known as forensic linguistic theory developed by Malcolm Coulthard. The data used are survey result among the francophone media consumers in Indonesia and articles originated from three different French alternative news media platform that have been identified as fake news by checking through fake news verification sites available on several investigator media platforms. These three articles are classified and analyzed using intertextuality and interdiscursivity methods within the forensic linguistic concepts. Critical perspective is used as the conceptual framework throughout this research. The results of the analysis show that 14.3% of respondents are not able to identify the fake news in the media they consumed. The linguistic features within 254 sentences contained deceits filtered from three medias tend to often use lexical morpheme components and syntactic patterns that provoke emotions and empathy in readers. Furthermore sentences structures are found in passive patterns frequently and use impersonal subjects as markers to a fewer references and cognitive complexity.
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