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Minimise risk to moderators of distressing content #511

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2 tasks
GeorgiaHCA opened this issue Jun 6, 2023 · 2 comments · Fixed by #677
Closed
2 tasks

Minimise risk to moderators of distressing content #511

GeorgiaHCA opened this issue Jun 6, 2023 · 2 comments · Fixed by #677

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@GeorgiaHCA
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Summary

Some moderators may have particular categories of content they would prefer not to see. It would be useful to find ways of minimising risk by flagging these before a human reads them.

What needs to be done?

  • Capture which terms or criteria could be used to flag content
  • Implement this so that moderators can opt out of seeing some posts.

Potential options:

  • filter posts with keywords
  • filter posts where the user has not flagged triggering content previously

Who can help?

Any suggestions welcome! Please add to the comments.

@GeorgiaHCA GeorgiaHCA added this to the 2: Create MVP milestone Jun 6, 2023
@gedankenstuecke gedankenstuecke removed this from the 2: Create MVP milestone Jun 16, 2023
@helendduncan
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This could be something that is addressed alongside #503?

@gedankenstuecke
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gedankenstuecke commented Jul 7, 2023

@helendduncan Do you mean by allowing keyword search on the experiences or by some more complex NLP to identify potentially triggering stories? My gut feeling is that it'll be really tough to reliably flag things based on this.

Instead of using keywords, I'd suggest using past publicly shared experiences as a proxy for whether a new story might or might not include triggers. In the simplest version of this we could add a bit of additional data to the moderation queue pages:

  1. Highlight if an experience is the first one ever submitted by a user (similar to how GH highlights first-time contributors). This will allow prioritizing newcomers to make sure the have a smooth experience, but also flag that they are most likely to not have experience with submitting (i.e. might not properly label an experience)
  2. Have a little flag of how many experiences submitted by a user have had trigger labels before (3/12 stories with warnings). It's not very granular, but allows moderators to make an informed guess that is not only based on the title.

EDIT: The other benefit of this approach is that it's technically rather easy to implement with our existing models etc.

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3 participants