Normalizing misogyny: hate speech and verbal abuse of female politicians on Japanese Twitter (original) (raw)
Related papers
Japan Forum, 2020
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.
2021
Social media platforms such as Twitter play an essential role in politics and social movements nowadays. The aim of this paper is to compare and contrast the language used on Twitter to refer to the candidates of the last UK general election of December 2019 in order to raise awareness of gender inequality in politics. The methodology followed is based on three aspects: (a) a quantitative analysis using Sketch Engine to extract the main collocates from the corpus; (b) a sentiment analysis of the compiled tweets by means of two lexicon classifications: BING (Hu & Liu, 2004) and NRC (Mohammad & Turney, 2013), which classifies words into eight basic emotions and two sentiments (positive and negative); and (c) a qualitative analysis employing a Critical Discourse Analysis approach (Fairclough, 2013) to examine verbal abuse towards women from a linguistics perspective.
Misogynistic Hate Speech on Social Networks: a Critical Discourse Analysis
PhD thesis, 2017
The present dissertation aims at recognising online misogyny as a form of hate speech, by providing a qualitative analysis of this discourse on Twitter and Facebook. While recent reports in media coverage have revealed that sexist harassment is the most pervasive social problem on Web 2.0, much scholarly research has mainly focused on other types of hate speech (e.g., racist and xenophobic vilification), overlooking the seriousness of misogynistic verbal abuse.
Is Japanese Gendered Language used on Twitter? A Large Scale Study
Online Journal of Communication and Media Technologies
This study analyzes the usage of Japanese gendered language on Twitter. Starting from a collection of 408 million Japanese tweets from 2015 till 2019 and an additional sample of 2355 manually classified Twitter accounts timelines into gender and categories (politicians, musicians, etc). A large scale textual analysis is performed on this corpus to identify and examine sentencefinal particles (SFPs) and first-person pronouns appearing in the texts. It turns out that gendered language is in fact used also on Twitter, in about 6% of the tweets, and that the prescriptive classification into "male" and "female" language does not always meet the expectations, with remarkable exceptions. Further, SFPs and pronouns show increasing or decreasing trends, indicating an evolution of the language used on Twitter.
The ever-increasing use of social media in African countries is celebrated as it has provided people with more spaces for dialogue and individual expressions. Whereas such ever-increasing of the accessibility and use of social media spaces offers users with freedom and democratic paradigms to comment, opine and debate on social, economic and political agenda, it has also resulted to increasing forms of sexist hateful speech. In so doing social media spaces have also changed the nature of communication, as a result, sexists appear to locate their discriminative voices in the new online spaces unlike in the traditional outlets and mainstream forums. This form of sexist hate speech incites gendered stereotypes of whom women often receive the extremes of the malpractices because of prevalence of patriarchal social set ups in most African societies. In most cases in Africa, sexist hate speech will be used as a weapon of gender-based violence means to bully women into silence and to maintain men's privileges. By using Content Analysis and Critical Discourse Analysis approaches, this study analyzed the linguistic clues of the sexist hate speech in Facebook and Instagram social networks. On the basis of selected open accounts of Tanzanian public figures and celebrities, this study particularly observed and interrogated on how language of the users embeds ideological and social construct in order to perpetuate and exacerbate gender inequality. The study partly examined sexist hate speech in the selected Russian social media to comparatively study how sexism is construed and perceived in the community.
2016
Nowadays, many celebrities use Instagram to connect with their fans. Unfortunately, for some celebrities, their popularity may not necessarily mean that they are liked by the public. The keyboard warriors, i.e. haters can freely hit the keyboard and leave hate comments as cyber communication does not require face-to-face interactions. Some of them even go so far by creating haters’ accounts of certain public figures, as can be found on @mulanjameelaqueen, created by the haters of Mulan Jameela, an Indonesian singer known for her affairs and unregistered marriage with her friend’s husband. This paper explores how being “another” woman is perceived in Indonesia. Mateo and Yus’ (2013) pragmatic taxonomy of insults was used as the framework of analysis. The data were taken from the captions and the comments of 10 of the most commented posts of @mulanjameelaqueen. They were processed by using AntConc to obtain the most frequently used words and their collocations, and the word clusters. ...
Politicians in the line of fire: Incivility and the treatment of women on social media
Research and Politics, 2019
A seemingly inescapable feature of the digital age is that people choosing to devote their lives to politics must now be ready to face a barrage of insults and disparaging comments targeted at them through social media. This article represents an effort to document this phenomenon systematically. We implement machine learning models to predict the incivility of about 2.2 m messages addressed to Canadian politicians and US Senators on Twitter. Specifically, we test whether women in politics are more heavily targeted by online incivility, as recent media reports suggested. Our estimates indicate that roughly 15% of public messages sent to Senators can be categorized as uncivil, whereas the proportion is about four points lower in Canada. We find evidence that women are more heavily targeted by uncivil messages than men, although only among highly visible politicians.
arXiv (Cornell University), 2024
Technology-facilitated gender-based violence has become a global threat to women's political representation and democracy. Understanding how online hate affects its targets is thus paramount. We analyse 10 million tweets directed at female candidates in the Brazilian election in 2022 and examine their reactions to online misogyny. Using a self-trained machine learning classifier to detect Portuguese misogynistic tweets and a quantitative analysis of the candidates' tweeting behaviour, we investigate how the number of misogynistic attacks received alters the online activity of the female candidates. We find that young and left-wing candidates and candidates with higher visibility online received significantly more attacks. Furthermore, we find that an increase in misogynistic attacks in the previous week is associated with a decrease in female candidates' tweets in the following week. This potentially threatens their equal participation in public opinion building and silences women's voices in political discourse.
Hatenography: An Analysis of Hate Speech on Facebook in 2019 Indonesian Presidential Campaign
Jurnal Komunikasi: Malaysian Journal of Communication, 2021
This article discusses hate speech on Facebook from two groups of supporters for the presidential candidates in the 2019 Presidential Election in Indonesia. The study used a virtual ethnography approach to analyze cultural groups or communities through their conversations on the Facebook platform. Data collection was conducted by observing and collecting words, phrases, and sentences in the Official Facebook account of two presidential candidates in the 2019 Presidential Election and statements of both presidential and vice-presidential candidates in 2019. In addition, researchers also observed three voluntary group accounts for each candidate. Therefore, the total number of accounts observed was eight. Data was analysed with Nvivo 12+ to obtain statistics on the strength of the chosen speech word and the dominant phrase or word that appears. The result shows that specific phrases or terms to intimidate each supporter of both parties in massive numbers appeared in the form of hate s...