Disqus helps Knight Lab gather feedback on Refine—Better Commenting

Earlier this week Disqus published an article about Knight Lab’s Refine—Better Commenting technology. The post is the first semi-tangible result of a conversation we started with Disqus many months ago and one that might help shape the future of the technology.

Refine—Better Commenting basically takes high-volume comment feeds (think CNN, where certain stories attract thousands of comments), analyzes them and provides users unique insight into what’s being discussed most.

From the Disqus post:

It can feel impossible, even futile, to sort through the conversation and figure out what people are really talking about when they’re responding to a story that has far reaching impact. While this is something we work to address with the Best sort option and user votes, the Knight Lab team from Northwestern University has taken it a step further.

The post goes on to describe the comments on a story about computer hacking:

Notably, of the top three non-article terms mentioned in the comments, none of them had to with hacking or security issues — they were (in order): “hoodie”, “Trayvon”, and “guy.” It seems that one significant response to the article had nothing to do with the content, itself, but rather, the image attached to the article. Results like this help reveal the collective sentiment of readers — the (Trayvon Martin) trial may be over, but it’s still very top of mind for many.

The Disqus post is an attempt by both Knight Lab and Disqus to figure out how much interest there would be in Refine—Better Commenting, and if there is interest, what aspects of the technology are most intriguing or useful.

Please take a look at the tool and feel free to provide some feedback, particularly if you’re a publisher or editor who deals with comments on news stories.

About the author

Ryan Graff

Communications and Outreach Manager, 2011-2016

Journalism, revenue, whitewater, former carny. Recently loving some quality time @KelloggSchool.

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