{"title":"推特# indonesia - terserah中愤怒表达的语用分析","authors":"Gabey Faustena Ulrikayanti","doi":"10.24071/ijels.v8i1.3886","DOIUrl":null,"url":null,"abstract":"This study attempts to identify the intention and pragmalinguistic forms of anger expression in tweets using #IndonesiaTerserah on November 15th, 2020. A corpus of 30 tweets is analyzed within pragmatic analysis framework. In analyzing the data, the illocutionary acts and pragmalinguistics forms of the tweets are the focus. The interpretation entails the analysis of text, addressing, and the identification of connotative meanings. The data are collected using Twitter Archiver Programme (API). An underlying assumption for choosing the time frame is the hashtag reached the highest trending in Indonesia as response to two mass gathering incidents in Soekarno Hatta airport on 10 November 2020, and Petamburan on 14 November 2020. Based on the findings of illocutionary act, the intention of using #IndonesiaTerserah in the tweets mostly is to state the fact and elaborate their opinions regarding the issues. The irritated feeling dominates the intention of using #IndonesiaTerserah. However, they also express expectation to the stakeholders to handle the issues in a better way. Based on the findings on pragmalinguistics forms, anger is expressed in thinly veiled form of cynical humor in order to make their message more straightforward to the addressees.","PeriodicalId":406723,"journal":{"name":"Indonesian Journal of English Language Studies (IJELS)","volume":"604 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pragmatics Analysis on Anger Expression in #IndonesiaTerserah on Twitter\",\"authors\":\"Gabey Faustena Ulrikayanti\",\"doi\":\"10.24071/ijels.v8i1.3886\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study attempts to identify the intention and pragmalinguistic forms of anger expression in tweets using #IndonesiaTerserah on November 15th, 2020. A corpus of 30 tweets is analyzed within pragmatic analysis framework. In analyzing the data, the illocutionary acts and pragmalinguistics forms of the tweets are the focus. The interpretation entails the analysis of text, addressing, and the identification of connotative meanings. The data are collected using Twitter Archiver Programme (API). An underlying assumption for choosing the time frame is the hashtag reached the highest trending in Indonesia as response to two mass gathering incidents in Soekarno Hatta airport on 10 November 2020, and Petamburan on 14 November 2020. Based on the findings of illocutionary act, the intention of using #IndonesiaTerserah in the tweets mostly is to state the fact and elaborate their opinions regarding the issues. The irritated feeling dominates the intention of using #IndonesiaTerserah. However, they also express expectation to the stakeholders to handle the issues in a better way. Based on the findings on pragmalinguistics forms, anger is expressed in thinly veiled form of cynical humor in order to make their message more straightforward to the addressees.\",\"PeriodicalId\":406723,\"journal\":{\"name\":\"Indonesian Journal of English Language Studies (IJELS)\",\"volume\":\"604 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Indonesian Journal of English Language Studies (IJELS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24071/ijels.v8i1.3886\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indonesian Journal of English Language Studies (IJELS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24071/ijels.v8i1.3886","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
本研究试图确定2020年11月15日使用#IndonesiaTerserah的推文中愤怒表达的意图和语用语言形式。在语用分析框架下对30条推文的语料库进行了分析。在数据分析中,以推文的言外行为和语用语言学形式为重点。口译需要分析文本、寻址和确定隐含意义。使用Twitter Archiver program (API)收集数据。选择时间框架的一个基本假设是,作为对2020年11月10日苏加诺哈达机场和2020年11月14日Petamburan机场两起大规模集会事件的回应,该标签在印度尼西亚达到了最高趋势。根据言外行为的调查结果,在推文中使用#印尼aterserah的意图主要是陈述事实,并阐述他们对这些问题的看法。愤怒的感觉主导了使用#印尼aterserah的意图。然而,他们也表达了对利益相关者以更好的方式处理问题的期望。基于对语用语言学形式的研究发现,愤怒以一种不加掩饰的愤世嫉俗的幽默形式表达,以使他们的信息更直接地传达给收件人。
Pragmatics Analysis on Anger Expression in #IndonesiaTerserah on Twitter
This study attempts to identify the intention and pragmalinguistic forms of anger expression in tweets using #IndonesiaTerserah on November 15th, 2020. A corpus of 30 tweets is analyzed within pragmatic analysis framework. In analyzing the data, the illocutionary acts and pragmalinguistics forms of the tweets are the focus. The interpretation entails the analysis of text, addressing, and the identification of connotative meanings. The data are collected using Twitter Archiver Programme (API). An underlying assumption for choosing the time frame is the hashtag reached the highest trending in Indonesia as response to two mass gathering incidents in Soekarno Hatta airport on 10 November 2020, and Petamburan on 14 November 2020. Based on the findings of illocutionary act, the intention of using #IndonesiaTerserah in the tweets mostly is to state the fact and elaborate their opinions regarding the issues. The irritated feeling dominates the intention of using #IndonesiaTerserah. However, they also express expectation to the stakeholders to handle the issues in a better way. Based on the findings on pragmalinguistics forms, anger is expressed in thinly veiled form of cynical humor in order to make their message more straightforward to the addressees.