{"title":"你很刻薄,但我喜欢它——丹马库评论中模仿不礼貌的元语用评价","authors":"Shengnan Liu","doi":"10.1016/j.dcm.2023.100700","DOIUrl":null,"url":null,"abstract":"<div><p>Mock impoliteness, a term encompassing a wide array of phenomena (e.g., banter, teasing, mocking, jocular mockery, jocular abuse/insults, humour, etc.), has long been grounded in the framework of (im)politeness. However, the research on the participants’ metapragmatic evaluations of mock impoliteness is scarce, with the exception of Sinkeviciute (2017). This research aims to investigate the third-party participants’ metapragmatic evaluation in Danmaku comments in a Chinese online talk show <em>Roast!</em> that features mock impoliteness speech events. Danmaku, as a commenting system that displays users’ synchronous comments within the video stream, is widely used in Asian countries, especially in China and Japan (Wu & Ito, 2014). Danmaku comments provide easy access to a vast amount of third-party participants’ evaluations of mock impoliteness, which is an ideal data source for this research. Such metapragmatic evaluations offer invaluable insight to the first-order understanding of mock impoliteness, which resonates with the discursive approaches to (im)politeness that advocates first-order understanding of (im)politeness interactions (Eelen, 2001; Locher and Watts, 2005; Locher, 2006, 2012, 2015; Mills, 2003). By qualitatively categorizing the information provided in the Danmaku comments, a data-driven coding scheme is created, which captures different aspects of information: (i) in-text reference (<em>Referent</em> and <em>Speech Event</em>); (ii) pragmatic phenomena that is relevant to mock impoliteness (<em>Impoliteness</em> and <em>Funniness</em>), and (iii) metapragmatic evaluation (<em>positive/negative Evaluation</em>). Then a conditional inference tree model (Hothorn et al., 2006; Tagliamonte and Baayen, 2012; Tantucci and Wang, 2018) was fitted to investigate to what extent the above factors contribute to third-party participants’ metapragmatic evaluations of mock impoliteness. This method generated clear data visualization by displaying the ranking of contributing factors to the metapragmatic evaluations. Such quantitative results were then interpreted through qualitative analysis of typical examples from the data. The analysis concludes that funniness and impoliteness are the two most statistically significant factors contributing to Danmaku users’ qualitative evaluations. This conclusion, in return provides solid empirical evidence for second-order theoretical underpinning of mock impoliteness.</p></div>","PeriodicalId":46649,"journal":{"name":"Discourse Context & Media","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"You’re so mean but I like it – Metapragmatic evaluation of mock impoliteness in Danmaku comments\",\"authors\":\"Shengnan Liu\",\"doi\":\"10.1016/j.dcm.2023.100700\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Mock impoliteness, a term encompassing a wide array of phenomena (e.g., banter, teasing, mocking, jocular mockery, jocular abuse/insults, humour, etc.), has long been grounded in the framework of (im)politeness. However, the research on the participants’ metapragmatic evaluations of mock impoliteness is scarce, with the exception of Sinkeviciute (2017). This research aims to investigate the third-party participants’ metapragmatic evaluation in Danmaku comments in a Chinese online talk show <em>Roast!</em> that features mock impoliteness speech events. Danmaku, as a commenting system that displays users’ synchronous comments within the video stream, is widely used in Asian countries, especially in China and Japan (Wu & Ito, 2014). Danmaku comments provide easy access to a vast amount of third-party participants’ evaluations of mock impoliteness, which is an ideal data source for this research. Such metapragmatic evaluations offer invaluable insight to the first-order understanding of mock impoliteness, which resonates with the discursive approaches to (im)politeness that advocates first-order understanding of (im)politeness interactions (Eelen, 2001; Locher and Watts, 2005; Locher, 2006, 2012, 2015; Mills, 2003). By qualitatively categorizing the information provided in the Danmaku comments, a data-driven coding scheme is created, which captures different aspects of information: (i) in-text reference (<em>Referent</em> and <em>Speech Event</em>); (ii) pragmatic phenomena that is relevant to mock impoliteness (<em>Impoliteness</em> and <em>Funniness</em>), and (iii) metapragmatic evaluation (<em>positive/negative Evaluation</em>). Then a conditional inference tree model (Hothorn et al., 2006; Tagliamonte and Baayen, 2012; Tantucci and Wang, 2018) was fitted to investigate to what extent the above factors contribute to third-party participants’ metapragmatic evaluations of mock impoliteness. This method generated clear data visualization by displaying the ranking of contributing factors to the metapragmatic evaluations. Such quantitative results were then interpreted through qualitative analysis of typical examples from the data. The analysis concludes that funniness and impoliteness are the two most statistically significant factors contributing to Danmaku users’ qualitative evaluations. This conclusion, in return provides solid empirical evidence for second-order theoretical underpinning of mock impoliteness.</p></div>\",\"PeriodicalId\":46649,\"journal\":{\"name\":\"Discourse Context & Media\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Discourse Context & Media\",\"FirstCategoryId\":\"98\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2211695823000338\",\"RegionNum\":2,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMMUNICATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discourse Context & Media","FirstCategoryId":"98","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2211695823000338","RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMMUNICATION","Score":null,"Total":0}
引用次数: 0
摘要
嘲笑不礼貌是一个涵盖广泛现象的术语(例如,玩笑、调侃、嘲讽、诙谐的嘲笑、诙谐的辱骂/侮辱、幽默等),长期以来一直以礼貌为基础。然而,除了Sinkevicuite(2017)之外,关于参与者对模拟不礼貌的元语用评价的研究很少。本研究旨在调查中国网络脱口秀节目《吐槽!以模仿不礼貌言语事件为特色。Danmaku作为一种在视频流中显示用户同步评论的评论系统,在亚洲国家,尤其是中国和日本被广泛使用(Wu&;Ito,2014)。Danmaku评论提供了大量第三方参与者对模拟不礼貌的评估,这是本研究的理想数据来源。这种元语用评价为模拟不礼貌的一阶理解提供了宝贵的见解,这与主张对礼貌互动进行一阶理解的(im)礼貌的话语方法产生了共鸣(Eelen,2001;Locher和Watts,2005;Locher,200620122015;Mills,2003)。通过对Danmaku评论中提供的信息进行定性分类,创建了一个数据驱动的编码方案,该方案捕获了信息的不同方面:(i)文本参考(参考和语音事件);(ii)与模拟不礼貌相关的语用现象(不礼貌和功能),以及(iii)元语用评价(积极/消极评价)。然后,拟合条件推理树模型(Hothorn et al.,2006;Tagliamonte和Baayen,2012;Tantucci和Wang,2018),以调查上述因素在多大程度上促成了第三方参与者对模拟不礼貌的元语用评价。该方法通过显示元碎片评估的贡献因素的排名来生成清晰的数据可视化。然后通过对数据中的典型实例进行定性分析来解释这些定量结果。分析得出结论,有趣和不礼貌是丹马库用户定性评价的两个最具统计学意义的因素。这一结论反过来为模拟不礼貌的二阶理论基础提供了坚实的经验证据。
You’re so mean but I like it – Metapragmatic evaluation of mock impoliteness in Danmaku comments
Mock impoliteness, a term encompassing a wide array of phenomena (e.g., banter, teasing, mocking, jocular mockery, jocular abuse/insults, humour, etc.), has long been grounded in the framework of (im)politeness. However, the research on the participants’ metapragmatic evaluations of mock impoliteness is scarce, with the exception of Sinkeviciute (2017). This research aims to investigate the third-party participants’ metapragmatic evaluation in Danmaku comments in a Chinese online talk show Roast! that features mock impoliteness speech events. Danmaku, as a commenting system that displays users’ synchronous comments within the video stream, is widely used in Asian countries, especially in China and Japan (Wu & Ito, 2014). Danmaku comments provide easy access to a vast amount of third-party participants’ evaluations of mock impoliteness, which is an ideal data source for this research. Such metapragmatic evaluations offer invaluable insight to the first-order understanding of mock impoliteness, which resonates with the discursive approaches to (im)politeness that advocates first-order understanding of (im)politeness interactions (Eelen, 2001; Locher and Watts, 2005; Locher, 2006, 2012, 2015; Mills, 2003). By qualitatively categorizing the information provided in the Danmaku comments, a data-driven coding scheme is created, which captures different aspects of information: (i) in-text reference (Referent and Speech Event); (ii) pragmatic phenomena that is relevant to mock impoliteness (Impoliteness and Funniness), and (iii) metapragmatic evaluation (positive/negative Evaluation). Then a conditional inference tree model (Hothorn et al., 2006; Tagliamonte and Baayen, 2012; Tantucci and Wang, 2018) was fitted to investigate to what extent the above factors contribute to third-party participants’ metapragmatic evaluations of mock impoliteness. This method generated clear data visualization by displaying the ranking of contributing factors to the metapragmatic evaluations. Such quantitative results were then interpreted through qualitative analysis of typical examples from the data. The analysis concludes that funniness and impoliteness are the two most statistically significant factors contributing to Danmaku users’ qualitative evaluations. This conclusion, in return provides solid empirical evidence for second-order theoretical underpinning of mock impoliteness.