Validity of German regional dialect markers for authorship profiling

用于作者分析的德国地方方言标记的有效性

• 批准号: 2401287
• 金额: --
• 依托单位: University of Birmingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2401287
• 关键词: Validity; German; regional; dialect; markers

Police and court cases in different jurisdictions involve understanding who the author of a piece of text is. The forensic linguistic discipline of authorship analysis (AA) tries to answer this question by inferring characteristics of authors from their writing (Juola 2007). This is based on the assumption that every use of language manifests the characteristics of its producer or their backgrounds (Coulthard & Johnson 2007). Language can therefore be used to profile an author by inferring information about the background of the author, e.g. gender or age (Argamon et al. 2007). However, profiling the regional background of an author has received limited attention in the literature (Shuy 2001), especially in a forensic context (Chambers 1990). Additionally, research on AA more generally has been predominantly on English (Shuy 2007). Thus, my focus will be on the degree to which regional dialect features are useful for profiling the regional background of authors of short online communications written in German. This will help advancethe best practices for authorship profiling and in forensic linguistics.My research goals are:- Analysing whether the textualisation of regional dialect features in German is sufficient to allow for regional profiling of online communication- Identifying the best regional dialect features in German for pinpointing the regional background of authors- Providing a procedure for supporting the regional profiling of German in AAThis project will utilise prior location analyses working with dialectal variation to predict location (Scheffler et al. 2014). I will identify a set of linguistic features for regional classification based on similar research in traditional German dialectology, including broad lexical distinctions between east/west and north/south (Niebaum & Macha 2014) and Gazetteer terms (Han et al. 2014), as well as grammatical and phonological textualisation of regional varieties (Herrgen 2019). These language markers will then be used to regionally classify a set of localised postings from social media communications (Hovy & Purschke 2018). The results will enable me to develop a procedure for best practice in authorship profiling cases.Ultimately, this project will have clear opportunity for societal impact. Finding the author of online communication is an everyday task for investigating agencies. Authorship profiling, especially for regional characteristics, can support and facilitate these tasks. Developing a procedure for best practice with known reliability rates would greatly benefit these forensic investigations. My research findings can be directly applied to cases of German authorshipanalysis and authorship profiling and help find authors of malicious online communication.

不同司法管辖区的警察和法院案件涉及了解一条文字的作者是谁。作者身份分析（AA）的法医语言纪律试图通过从作者的写作中推断出作者的特征来回答这个问题（Juola 2007）。这是基于以下假设：语言的每一次使用都表现出其生产者或背景的特征（Coulthard＆Johnson 2007）。因此，可以通过推断有关作者背景的信息，例如性别或年龄（Argamon等，2007）。但是，对作者的区域背景进行分析在文献中受到了有限的关注（Shuy 2001），尤其是在法医背景下（Chambers 1990）。此外，对AA的研究通常主要是在英语上（Shuy 2007）。因此，我的重点将放在区域方言特征在多大程度上可用于介绍用德语编写的简短在线通信作者的区域背景。 This will help advancethe best practices for authorship profiling and in forensic linguistics.My research goals are:- Analysing whether the textualisation of regional dialect features in German is sufficient to allow for regional profiling of online communication- Identifying the best regional dialect features in German for pinpointing the regional background of authors- Providing a procedure for supporting the regional profiling of German in AAThis project will utilise prior location analyses working with方言变化以预测位置（Scheffler等，2014）。我将根据传统德国辩证法的类似研究来确定一组区域分类的语言特征，包括东/西部和北/南/南/南/南部（Niebaum＆Macha 2014）和Gazetteer术语（Han等，2014）之间的广泛词汇区别，以及区域性品种（Herrgen 2019）的语法和语音文本化。然后，这些语言标记将用于区域对社交媒体传播的本地化帖子进行分类（Hovy＆Purschke 2018）。结果将使我能够在作者身份概况中制定最佳实践程序。一定，该项目将有明显的社会影响机会。寻找在线沟通的作者是调查机构的日常任务。作者身份分析，尤其是对于区域特征，可以支持和促进这些任务。开发以已知可靠性率的最佳实践程序将极大地使这些法医调查受益。我的研究发现可以直接应用于德国作者制分析和作者身份分析的案例，并帮助找到恶意在线交流的作者。