Digital Food Talk

IF 0.1 4区 文学 0 LITERATURE
S. Rüdiger
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引用次数: 0

Abstract

Watching someone else eat online – a phenomenon which originated in South Korea around the year 2008 (Donnar 2017, 122) – has become a popular video genre around the world. These shows are generally known as Mukbang, with the name reflecting their Korean origin (a blend of the Korean words 먹는, meokneun, 'eating' and 방송, bangsong, 'broadcast'). While the portion size of the consumed foods may vary from show to show and from performer to performer, typical Mukbang feature excessive food consumption and overeating (see section 2.1 for an example). Recently, the extremity of this has led China to censor Mukbang videos on a variety of platforms due to concerns about food waste and food security (Tidy 2020); users in China searching for Mukbang online are now shown a warning notice and some social media companies reacted by blurring the videos to make them less appealing (Tidy 2020). Other criticism concerns the shows' potential involvement in the formation and normalization of eating disorders (see, e.g., Strand and Gustafsson 2020) and internet addiction (Kircaburun et al. 2020). However, Mukbang watching has also been reported to have positive effects on food intake (i.e., encouraging more food intake for groups where this is desirable, or, conversely, preventing binge eating) and to alleviate feelings of loneliness (Strand and Gustafsson 2020, 606). Mukbang are thus a complex phenomenon and their societal impact makes it important to study them in-depth and from various perspectives; nevertheless, linguistic investigations of Mukbang (including subtypes and related genres) remain rare (but cf. Choe 2019; Choe 2020 for Korean-language shows and Rüdiger 2020; Rüdiger 2021 for English-language shows). This paper aims at further filling this gap by approaching this format from the perspective of immediacy and distance. More specifically, despite being produced primarily in the spoken mode, eating shows constitute a fascinating mix of characteristics associated with immediacy and distance (cf. also the notion of 'tertiary orality;' see Heyd, this issue). We will see this in the application of the model of communicative immediacy and distance (Koch and Oesterreicher 1985/2012) and Landert and Jucker's (2011) enriched communicative model to YouTube eating shows later on in this paper. In addition to this modelling (drawing on a corpus of eating shows), the comment replies by eating show performers in the videos' comments sections will also be included in the analysis. First, this paper introduces the eating show genre from the perspective of performative food consumption in general and outlines its development, characteristics, and diversification. Section 3 presents a brief overview of the aforementioned communicative models, which will be applied to the eating shows in the analysis (i.e., Koch and Oesterreicher 1985/2012; Landert and Jucker 2011). Section 4 is then devoted to the methodology and section 5 constitutes the analysis, which is divided into
数码美食讲座
“看别人在网上吃饭”这一现象在2008年左右起源于韩国(Donnar 2017, 122),现已成为一种流行的视频类型。这些节目通常被称为“吃包”,这个名字反映了它们的韩语起源(由韩语单词“烹调”、“吃”和“广播”组合而成)。虽然每一场表演和表演者所消耗的食物的份量可能会有所不同,但典型的Mukbang的特点是过度的食物消耗和暴饮暴食(见2.1节的例子)。最近,由于担心食物浪费和粮食安全,中国在各种平台上审查Mukbang视频(Tidy 2020);中国用户在网上搜索Mukbang时,会看到一个警告通知,一些社交媒体公司的反应是模糊视频,使其不那么吸引人(Tidy 2020)。其他批评关注的是这些节目可能参与饮食失调(例如,Strand和Gustafsson 2020)和网络成瘾(Kircaburun et al. 2020)的形成和正常化。然而,据报道,看Mukbang对食物摄入也有积极影响(即鼓励更多的食物摄入,或者相反,防止暴饮暴食),并减轻孤独感(Strand and Gustafsson 2020, 606)。因此,Mukbang是一个复杂的现象,其社会影响使得从各个角度深入研究它们变得很重要;然而,对Mukbang(包括亚型和相关体裁)的语言学研究仍然很少(但cf. Choe 2019;韩国语节目“Choe 2020”和“rdiger 2020”;rdiger 2021(英语节目)。本文旨在从即时性和距离性的角度探讨这一格式,进一步填补这一空白。更具体地说,尽管主要是以口头方式制作的,但饮食节目构成了与即时性和距离感相关的迷人混合特征(参见“第三口头性”的概念;见Heyd,本期)。我们将在本文后面将交际即时性和距离模型(Koch and Oesterreicher 1985/2012)和Landert and Jucker(2011)的丰富交际模型应用于YouTube饮食节目中看到这一点。除了这个模型(从饮食节目的语料库中绘制)之外,饮食节目演员在视频评论部分的评论回复也将包括在分析中。首先,本文从表演性食品消费的总体角度对吃秀类型进行了介绍,并概述了它的发展、特点和多样化。第3节简要概述了上述交际模型,这些模型将应用于分析中的饮食节目(即Koch和Oesterreicher 1985/2012;Landert and Jucker 2011)。然后,第4节专门讨论方法,第5节构成分析,分为
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来源期刊
CiteScore
0.30
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0.00%
发文量
30
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