Migration and Patterns of Hate Speech in Social Media - A Cross-cultural Perspective

在西方社会，移徙问题往往伴随着公众的高度焦虑，并转化为针对移民和少数群体的仇恨言论的大量增加。社交媒体似乎是仇恨言论的沃土。M-PHASIS项目侧重于仇恨言论的社会层面，力求研究用户生成内容中与移民有关的仇恨言论的模式。该项目将涉及以下方面，以更好地了解法国和德国用户生成内容中仇恨言论的流行和出现情况： 通过考虑这一现象的多种特征（仇恨言论的词汇、句法和语境方面）并考虑到显性和隐性形式，推进对仇恨言论的理解和评估。 制定一项研究协议，以检测文本中的仇恨言论，并根据其所指对象对其进行分类（即，与仇恨言论相关的主题）和所传达的表达方式，以及其循环特征。 在效度、信度和跨文化等效性方面改进仇恨言论检测方法. 对法国和德国仇恨言论的流行程度以及导致两国仇恨言论的因素进行跨文化比较（例如，评论出现的平台，周围用户生成的上下文的同质性，新闻干预）。 继续对社交媒体来源的仇恨言论的真实例子进行存档和注释，并在项目结束时发布给研究界进行二次分析。我们的研究假设是，社交媒体中针对移民的仇恨言论：● 是上下文相关的：必须结合其周围的主题内容、支持媒体渠道以及其出现的社会文化条件来理解和分析它。 仇恨言论以不同的方式表现出来，并且可以系统化：仇恨言论可以通过其语言特征来理解，但也可以是含蓄的，以更微妙的方式传达。因此，在这个项目中，我们想研究什么类型的语境与什么类型的仇恨言论有关。该项目采用跨学科方法实现其目标，并寻求利用计算机处理社交媒体中仇恨言论所提供的投入。所获得的见解将允许产生一个软件应用程序检测和/或自动阻止仇恨的评论。在这个项目期间开发的资源将在开放获取平台上提供给科学界。将实施一个网络演示器，以验证项目中取得的科学发展。

Within Western societies, the issue of migration is often accompanied by high levels of public anxiety and translates to a significant increase of the use of hate speech towards immigrants and minorities. Social media seem to be a fertile ground for hate speech. Focusing on the social dimension of hate speech, the project M-PHASIS seeks to study the patterns of hate speech related to migrants in user-generated content. The project will address the following aspects to provide a better understanding of the prevalence and emergence of hate speech in user-generated content in France and Germany:1. Advance the understanding and assessment of hate speech by considering multiple features of the phenomenon (lexical, syntactical and contextual facets of hate speech) and taking into account explicit and implicit forms.2. Develop a research protocol to detect hate speech in text and classify it in terms of its referents (i.e., themes associated with hate speech) and the representations conveyed, as well its circulatory characteristics.3. Improve the methods to detect hate speech in terms of validity, reliability, and the equivalence across cultures.4. Conduct a cross-cultural comparison of the prevalence of hate speech in France and Germany and the factors that give rise to hate speech in both countries (e.g., platforms on which comments appear, homogeneity of surrounding user-generated context, journalistic intervention).5. Proceed to the archiving and annotation of real-life examples of hate speech from social media sources, to be released to the research community for secondary analyses at the end of the project.Our research hypotheses are that hate speech against migrants in social media:● Is context-dependent: it must be apprehended and analyzed in relation to its surrounding topical contents, its supporting media outlets as well as the sociocultural conditions of its appearance.● Materializes in different ways that can be systematized: hate speech can be understood through its linguistic features but can also be implicit, conveyed in more subtle manners.In this project, we therefore want to examine what types of contexts relate to which types of hate speech. The project embraces an interdisciplinary approach to its object and seeks to benefit from the inputs provided by computerized processing of hate speech in social media. The insights gained will allow to produce a software app detecting and/or blocking hateful comments automatically.Resources developed during this project will be made accessible in Open Access Platforms to the scientific community. A web demonstrator will be implemented to validate the scientific developments achieved in the project.