Abstract

Social media platforms such as Twitter have gained tremendous political importance in recent years. Moreover, being considered as platforms for organizing grass root political movements or political participation in general, this positive view has given way to more critical perspectives on the negative sides of social media, such as attempts of algorithmically manipulating public opinion or the outcome of elections and racist or sexist hate speech. For the case of Japan, despite particularly xenophobic hate speech on bulletin boards such as “2channel” (ni-channeru) or Twitter has been extensively studied from various angles, misogynic forms of verbal abuse towards females on social media, female politicians in particular, have received much lesser attention in existing research. In this article we present results from an explorative analysis of instances of misogynist or sexist hate speech and abusive language against female politicians on Twitter, applying computational corpus-linguistic tools and methods, supplemented by a qualitative in-depth study of verbal abuse of four prominent female politicians, namely Renhō, Tsujimoto Kiyomi, Yamao Shiori, and Koike Yuriko, thereby fruitfully combining quantitative-statistical and qualitative-hermeneutic approaches.

摘要

近年来，Twitter 等社交媒体平台获得了巨大的政治重要性。此外，被视为组织基层政治运动或一般政治参与的平台，这种积极的观点已经让位于对社交媒体消极方面的更批判性观点，例如试图通过算法操纵舆论或选举结果和种族主义或性别歧视的仇恨言论。就日本而言，尽管“2channel”（ni-channeru) 或 Twitter 已经从各个角度进行了广泛的研究，在现有的研究中，社交媒体上对女性，特别是女性政治家的厌女形式的辱骂形式受到的关注要少得多。在本文中，我们展示了对 Twitter 上针对女性政治家的厌恶女性或性别歧视的仇恨言论和辱骂性语言的实例的探索性分析结果，应用计算语料库语言工具和方法，辅以对四个突出的语言辱骂的定性深入研究女性政治家，即 Renhō、辻本清美、Yamao Shiori 和 Koike Yuriko，从而卓有成效地结合了定量统计方法和定性解释方法。