Linguistic Errors of Indonesian Air Transportation Hoax

Y. A. Pinem
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Abstract

The research was to find out linguistics’ indicators of errors found in the body content of false news discourse mingling around air transportation issues that appeared 2-years before the presidential election in 2019. The qualitative research used hoax discourse from the turnbackhoax.com collection. Errors found in discourse were later generated according to linguistics’ domain in Dulay et al., as well as additional spelling errors and surface strategy taxonomy. Toward false news (n=44) found in the data source, errors majorly emerge in newly ungrammatical word formation with omission process equitably distributed in all linguistics’ domains. Errors in phonology portray localization in several dialects in Indonesia, while errors in morphology and syntax appear for language economy purposes. Primarily affected, lexicon and semantics is the domain with the most variant of surface structure errors (n=4). This is relevant to the hoax spread’s intended purpose to deceive the audience by modifying words in originally true news to give different content meanings. Omission resulting in word shortening in the form of blending and clipping with 98% occurrences is popularly used by millennials with a medium level of media literacy to communicate in the digital society environment. To enhance relatedness in readers’ thoughts and feelings, explain errors that deliberately happened in pragmatics and spelling. Being familiar with these indicators can alert the public to question a post’s credibility, thus encouraging the urge for clarification.
印尼航空运输骗局的语言错误
这项研究旨在找出语言学在2019年总统大选前两年出现的围绕航空运输问题的虚假新闻话语的正文内容中发现的错误指标。定性研究使用了turnbackhops.com收集的恶作剧话语。后来,根据Dulay等人的语言学领域,以及额外的拼写错误和表面策略分类法,在语篇中发现了错误。对于在数据源中发现的假新闻(n=44),错误主要出现在新的不符合语法的单词形成中,省略过程在所有语言学领域中公平分布。音韵学上的错误反映了印度尼西亚几种方言的本地化,而形态学和句法上的错误则是出于语言经济的目的。词汇和语义是表面结构错误变化最多的领域(n=4)。这与恶作剧传播的目的有关,即通过修改原本真实的新闻中的词语来赋予不同的内容含义来欺骗观众。在数字社会环境中,具有中等媒体素养的千禧一代普遍使用省略,以混合和剪辑的形式缩短单词,出现率为98%。为了增强读者思想和情感的相关性,解释语用学和拼写中故意发生的错误。熟悉这些指标可以提醒公众质疑帖子的可信度,从而鼓励人们澄清。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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