Normalizing misogyny: hate speech and verbal abuse of female politicians on Japanese Twitter

Politicians, Social Media, and Digital Publics: Old Rights, New Terrain

“…They did not, in contrast to Stambolieva, find statistically significant racial or ethnic differences. Beyond the United Kingdom, studies have found that female politicians in Italy are targeted by more hostile language on Facebook (Pacilli & Mannarini, 2019), that female politicians in Japan are targeted with hate speech and verbal abuse (Fuchs & Schäfer, 2019), and that in the United States, female legislators are more often the targets of hostility on Twitter than their male counterparts, with particularly egregious hostility directed at female legislators of color, much of it explicitly identity-based, drawing on racist and sexist stereotypes and epithets (Sobieraj & Merchant, in press) Setting aside the volume of abuse, among these studies there seems to be a general consensus that the vitriol directed at officeholders from underrepresented groups is qualitatively different from that faced by those from dominant groups in ways that amount to sexual, racial, and religious harassment. In the United States, this is visible in recent high-profile attacks against representatives Ilhan Omar (D-MN) and Alexandria Ocasio-Cortez (D-NY), both of whom have endured venomous, identity-based abuse online.…”

“…They did not, in contrast to Stambolieva, find statistically significant racial or ethnic differences. Beyond the United Kingdom, studies have found that female politicians in Italy are targeted by more hostile language on Facebook (Pacilli & Mannarini, 2019), that female politicians in Japan are targeted with hate speech and verbal abuse (Fuchs & Schäfer, 2019), and that in the United States, female legislators are more often the targets of hostility on Twitter than their male counterparts, with particularly egregious hostility directed at female legislators of color, much of it explicitly identity-based, drawing on racist and sexist stereotypes and epithets (Sobieraj & Merchant, in press)…”

Determining Public Opinion of the COVID-19 Pandemic in South Korea and Japan: Social Network Mining on Twitter

“…The final analysis included 1,470,313 tweets from Korea and 4,195,457 tweets from Japan; the daily Japanese tweets were limited because of their volume. Most Japanese citizens mainly use Twitter as SNS [16] rather than Facebook or Instagram, whereas the ranking of Twitter usage rate by Koreans is 7th (0.2%), which is relatively lower than Japan [17]. This may be due to the difference in populations: the current population of Japan (126,264,931) is 2.4 times higher than Korea (51,709,098) [18].…”

Users Hate Blondes: Detecting Sexism in User Comments on Online Romanian News

“…There are other similar approaches analysing how sexism manifests in different environments: at the workplace (Grosz and Céspedes, 2020), in the gaming communities (Ghosh, 2021), in politics (Gorrell et al, 2020;Fuchs and Schäfer, 2020). Several shared tasks are dedicated to the identification of online sexism and misogyny: sEXism Identification in Social neTworks (EXIST) (Rodríguez-Sánchez et al, 2021), Automatic Misogyny Identification at IberEval (Fersini et al, 2018) and Evalita (Fersini et al, 2020) and Multimedia Automatic Misogyny Identification (MAMI) (Fersini et al, 2022).…”