Introduce yourself!


Thanks Ted. We’ve had a discussion about metrics before on here. I’ve yet to see any definitive answers emerge.

Here’s where we’ve got to in four different discussions/pieces - do add any thoughts you have:

There’s also something really compelling about communities focused around Q+As and collaborative problem solving. To what extent do you think news organizations can harness something similar, beyond mostly-one-directional AMAs?


Hi everyone!

My name is Jon. I work in tech for a PR firm. Though my background is in software development, the behavioral research and non-tech aspects of the project are most intriguing. I’m looking forward to increasing my participation and to get the word out about the project.


Hi Jon,

I’m Sydette the Coral Project community lead .Welcome. So glad to have you !

Why do those parts intrigue most ? Is there anything we’re doing you see that could be really useful in PR?


Hi Sydette -
So many times it happens that institutions throw technology at a problem and ignore the people component. That the Coral Project is including social (people) aspects is rather unusual and refreshing.

What parts, you ask? When I was first exposed to Project Coral a year ago, I read something about how comment civility increases when the journalist that wrote the piece engages in the comments. I wish I could remember the source.


My name is Randall. I worked for four years as the founding engineer of the Hypothesis Project and have been part of the Web Annotation Working Group at the W3C.

I’m interested in pushing the envelope of what is possible with web publishing tools, especially commenting, collaborative authoring, and journalistic research.

Looking forward to following along with the work of the Coral Project!

You can find me as @tilgovi here and on Twitter and GitHub.


HI Randall,

Welcome! to the Community. We’ve spoken to Hypothesis and I love annotation because I am a history nerd,What are the spaces you think have the most possibility?.What really excites you in the space? I’m really interested in encouraging community info sourcing as annotation in articles .


I’m really excited to see the Web Annotation specs stabilize, and see implementations happening all over the place. I really hope it succeeds in becoming a technical recommendation of the W3C. It’s not so much that I have particular hopes for strong tool interoperability as much as the re-usability that a common vocabulary brings to projects and modules. I have hope that some of the ES6 modules I’ve written for the HTML environment will actually find use in EPUB readers and such.

As far as user experience and products go, I am actually really excited to see the Clipboard APIs advancing in the browser, and I hope Chrome and IE implement custom MIME types for the clipboard soon. I think cross-frame communication is one of the hardest parts of browser extensions and third party site add-ons, but for interactive reading and writing we have this really wonderful bus (cross-application, even) that has been underutilized for decades.

I’m also inspired by full-text search like what is trying to do.

A mash-up of these ideas is something I’d like to see. Rather than ambitiously indexing all that a user sees, keep track only of highlighted or copied snippets and offer to auto-complete or paste them with reference in editors. We’re all familiar with auto-completed @ mentions and # hashtags, but why not quotes? The storage and privacy concerns are greatly reduced this way and it becomes tenable even in a mobile environment, I think.

Anyway, that’s enough rambling. Part of what excites me about Coral is that it’s tackling community problems really directly and those problems were often derailing when I was trying to focus on reading/writing workflow. Specialization, composability, and mash-ups with the right level of platform support have much more promise to me.


Hi Andrew,

Somehow I missed this very thoughtful reply - and only got to really dig into it now. The quality question is a really interesting one, that I’m not sure anyone has really “solved.” We tend to recommend to CMs that they don’t get wrapped around the axle of scoring/judging every reply, because it quickly becomes overwhelming. But developing standards for behavior, and recognizing the comments that come closest to that is valuable… if often subjective.

The journalism context adds an interesting layer to the discussion of collaboration. I see from my perspective great opportunity for news organizations to harness the expertise and energy that they are uniquely situated to bring together to solve problems. One way that some organizations are helping to level the discussion (and get people connecting on less conflict-centered levels, is through items such as “Working Out Loud” threads, simply sharing what they are working on without judgment. That can lead to offers of shared resources and surfacing of different perspectives that can lead to truer collaboration. If one side has all the Qs and the other has all the A’s, it’s not as much a discussion, as a lecture.

Great items to explore!


I like this a LOT!!!


doing a lot of catch-up on this thread the past few days. this topic, alone, is a solid trove. Running into you here is delightful, John. hope to find you’re still active in these Coral Project discussions.

It is intriguing – not daunting – that we’re still pursuing the grail of effective communities WELL after your early work. We haven’t yet perfected them in the material world; we shouldn’t expect adding the digital layer of abstraction makes it any more straightforward. Looking forward to seeing / learning more from you here -


Hello Everyone,

Coral Project looks amazing.

My name is Vigneshwer have been a mozillian for the past 4 years, I am an AI engineer from Bengaluru India thinking about the impacts and opportunities of ML in journalism.

Looking forward to discussing new parameters for better decision making in the journalism industry.


Hello! Vigneshwer!

Yeah , We love when mozillians arrive. What do you think is the biggest opportunity in journalism with in you fields? What facets of journalism concern you most when it comes to community impact?


Hi Vigneshwer! Great to have you here. A good place to start to think about ML combined with NLP in this area is @nad’s reading list on artificial moderation: and Francis Tseng’s work on metrics:

We’re not using ML to start with in our team, so there’s plenty of room for experimentation.

We’d love to hear more of what you’re thinking!




Hi @sydette,

I got to know about the coral project the other day when @andrew_coral had posted in one the discourse channel where Mozillians are very active.

What do you think is the biggest opportunity in journalism within you fields?

According to me data science and journalism goes hand in hand and has seen some really good works in the recent year, but AI for journalism is something huge and people haven’t actually thought about it much. I would like to think about platforms & services which are predicting the future news for me and my stakeholders based on the environment I create for it to learn from (By environment I am talking about twitter & other news data sources)

What facets of journalism concern you most when it comes to community impact?

I feel investigative journalism has huge impacts on the community and their perspectives, also there is a lot of room for automation of relevant news (data) collection and benchmarking the sources in this area.


WOW !! These blogs on artificial moderation and metrics look really amazing :slight_smile:

I am gonna sit back and read them completely, then will post my views & ideas here.

Thanks @andrew_coral for sharing them. I would like to collaborate and contribute in code & ideation on such experimentations, let me know if any such thread is on !!


When you say predicting the news do you mean predicting relevant stories?

Because i could see building solid communities around that kind of community taught AI


I am thinking beyond just relevant stories, that pretty easy like that not AI right !!

Prediction of an event can be something like guessing an event/story in a simulation environment by an algorithm the way it would work is that the researcher would have collected some past activities/ actions (which would be the training data) and on that the algorithms have learned some metrics/ feature out of them.

Say a simple real world example would be to train an algorithm to classify between a fake and real news from twitter data.


Hello! I’m Lisa, and I’m part of the Corporate Development team at Politico. We work on acquisitions, partnerships, and growth initiatives. I came across the Coral Project and am really interested in what you’re doing – we’re always looking for ways to better engage our audience.


Welcome Lisa,

What are the areas you think have the most opportunity for growth in audience relations? Political topics are the most contentious and I am constantly thinking of things between polls and open comments to exchange ideas without vitriol. What concerns you most ?


There are various discussions on metrics around the community - you can search in the top right, clicking on the magnifying glass. Here’s a few starting points: