Buzzword: 撕漫感 manga-ish, cartoonish
撕漫感 sīmàn gǎn
If we break down the expression word by word, “撕” means “to tear, to rip” in English and “漫” refers to Japanese manga. The newly-coined expression is used to describe people who looks or dressed up pretty much resembling certain characters in comics, Japanese manga and anime series. Different from cosplay aficionados, these people, usually good looking, did not mean to dress up as manga characters on purpose. It can also refer to fashion, clothing designs or accessories that are exaggerated or surreal that are often found in fantasy anime and mangas.
Tàilè Sīwēifūtè de mǎwěibiàn zàoxíng shénsì rìmàn Fate xìliè lǐ de Saber, yǒu zhǒng sīmàn gǎn.
The look of Taylor Swift in her ponytail is quite manga-ish, pretty much resembling the character Saber in Japanese manga series “Fate.”
The reaped post-90s generation, the well-fleeced post-90s flock
Sharing the same pronunciation in mandarin Chinese, “韭零后” is a playful homophonic term to “九零后,” aka the post-90s generation. The expression becomes popular among young Chinese in recent days, who ironically comparing themselves to “韭菜,” or Chinese leeks. The self-mockery comes from a common Chinese slang “割韭菜,” meaning “to reap the leeks” in English. The plant has a short growth period, lasting about 3-4 months. Fully-grown Chinese leeks can be harvested consecutively in spring. Thus, “韭菜” is now frequently used to describe well-fleeced retail investors who have been repeatedly played for the suckers, or consumers prone to getting scammed or exploited. The year 2020 saw a craze for fund investment in China, when high-income, tech-savvy post-90s retail investors flocking to the market to make a profit. However, a growing number of young investors got trapped as the fund market slide continues since the beginning of this year. The expression vividly outlines the frustration and regrets of these young investors.
Lèguān de jiǔlínghòu huà kuīqián wéi dàliàng de duànzi.
Those optimistic post-90s retail investors, though well-fleeced, wrote countless memes based on their bad investments.