tags: cofacts, meeting note GA: UA-98468513-3 —

20210505 會議記錄

:::info

:potable_water: Release pipeline

:star: Released to production

:robot_face: rumors-line-bot

2021/05/05 Release

:rocket: Staging

:globe_with_meridians: Site

防詐顯名

趨勢 4/29 停止接取 Cofacts –> verified.

LIFF article page

  1. Article LIFF 設計 https://www.figma.com/file/DvmAQjMJCncuPORWKnljM1/?node-id=3004%3A224
  2. 實作 article & reply
  3. 實作 feedback form
  4. 實作 reply request list & form
  5. 實作 related article

Syndavant 貼圖

會用較粗的線繪製

Japanese version Cofacts

好像其實是想做 AI(QA 系統與情緒分析),日本版 Cofacts 只是順便?

https://g0v-slack-archive.g0v.ronny.tw/index/channel/C2PPMRQGP/2021-05#ts-1619953182.0885

Thanks! I’ll check the article out really interested to take a look into this research. Wondering if there are models that could be used to detect strongly emotional messages that would be typically associated with fake information [name=John Cronin-McCartney]

As far as I know Cofacts never tried to detect emotion in rumor text. Institute for Information Industry do develop such feature in Rumor Catcher ( https://tfc-taiwan.org.tw/articles/4477 ). However, they are not a fan of open-source and want to hold their findings proprietary. Another direction may be Squash https://www.niemanlab.org/2020/07/a-lesson-in-automated-journalism-bring-back-the-humans/ and Full Fact https://fullfact.org/blog/2020/jul/afc-global/ [name=mrorz]

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