Re: long time no chat, CredWeb friends

We have at this point built systems and published several papers 
demonstrating our proposed approach:

 1. users indicate who they trust (privately)
 2. users assess information as accurate or inaccurate (publicly)
 3. users can filter information based on assessments from people that
    they trust, e.g. "exclude information assessed as false by people I
    trust" or "only show information assessed as true by people I trust"
    or "show me information where people I trust disagree with each other".

We created a prototype social platform <http://trustnet.csail.mit.edu/> 
where this methodology is applied to posts on the platform, as well as a 
chrome browser extension 
<https://chrome.google.com/webstore/detail/trustnet/nphapibbiamgbhamgmfgdeiiekddoejo> 
that applies this methodology to all pages on the web, as well as all 
the posts in your facebook and twitter feeds, and another extension 
<https://chrome.google.com/webstore/detail/reheadline/iignpdlabbnnacdkchpnpljkhdlkblbh> 
that lets people you trust edit the headlines of articles on the web 
(and link anchor text) to improve their accuracy.  My student Farnaz who 
led the work is beginning a professorship at U Michigan.

We carried out small experimental deployments that showed positive 
results, and I would love to talk to and collaborate with anyone who has 
ideas about more substantial experiments than run longer or with larger 
groups.

Papers:
Farnaz Jahanbakhsh, Amy X. Zhang, Adam J. Berinsky, Gordon Pennycook, 
David G. Rand, and David R. Karger. 2021. Exploring Lightweight 
Interventions at Posting Time to Reduce the Sharing of Misinformation on 
Social Media. Proc. ACM Hum.-Comput. Interact. 5, CSCW1, Article 18 
(April 2021), 42 pages. https://doi.org/10.1145/3449092

Farnaz Jahanbakhsh, Amy X. Zhang, and David R. Karger. 2022. Leveraging 
Structured Trusted-Peer Assessments to Combat Misinformation. Proc. ACM 
Hum.-Comput. Interact. 6, CSCW2, Article 524 (November 2022), 40 pages. 
https://doi.org/10.1145/3555637

Farnaz Jahanbakhsh, Amy X. Zhang, Karrie Karahalios, and David R. 
Karger. 2022. Our Browser Extension Lets Readers Change the Headlines on 
News Articles, and You Won't Believe What They Did! Proc. ACM 
Hum.-Comput. Interact. 6, CSCW2, Article 530 (November 2022), 33 pages. 
https://doi.org/10.1145/3555643



On 10/23/2023 1:01 PM, Scott Yates wrote:
> You are getting this email because at some point you were a part of 
> the CredWeb group in W3C, started by the incomparable Sandro Hawke.
>
> Then I came in and tried to create a new mission for the group, and 
> then we all just moved on.
>
> This group is now going to get deleted unless we find a new source of 
> inspiration and leadership, but before we do that... maybe we could 
> just get together to get quick updates on what we've all been doing?
>
> Let's do it at the time we used to do it: this Wednesday at 4 p.m. in 
> London, 11 a.m. Eastern, 8 a.m. in California.
>
> Here's a Google Calendar link. 
> <https://calendar.google.com/calendar/event?action=TEMPLATE&tmeid=NWxmcmJtYWhwajBpbmt1dWVtZmYzNm04bzUgc2NvdHRAam91cm5hbGxpc3QubmV0&tmsrc=scott%40journallist.net>
>
> I hope to see a lot of you there! If you can't make that time, feel 
> free to drop Sandro and me a note and let us know what you are up to, 
> and if you have any thoughts about keeping the CredWeb group going.
>
> -Scott Yates