A Closer Look: Did #wddchat14 Feature the Whole World?

Our friends at the Diabetes Community Advocacy Foundation, moderators of the #dsma Twitter chat, hosted a 24-hour conversation on World Diabetes Day, featuring the hashtag #wddchat14. The objective of this chat was to have 24 moderators host 24 topics from 12:00 a.m. EST on Thursday, November 14 to 12:00 a.m. EST on Friday, November 15. Obviously the expectation that a single person would participate in the entire day-long conversation is unrealistic – after all, we have lives to lead. But, in theory, a chat taking place over the course of a 24-hour window should provide everyone, across the world, an opportunity to participate is one worth pursing. And for the sake of this blog post, it’s one worth investigating.

Is it possible to host a truly worldwide conversation on Twitter? Do certain countries dominate participation, regardless of the time of day? What can be learned from an effort like this?

Over the course of the entire 24-hour period, 602 participants engaged with the #wddchat14 hashtag, supplying 6,709 tweets, and generating 20,000,726 impressions. Those numbers are great, but I was curious about the specific location of the participants – after all, it’s called World Diabetes Day.

Before I share the data, you will need a little context for how everything is gathered. Symplur Signals is able to tag a user and their associated tweets with a location provided that user has a valid, actual location entered in their profile. Countries and states that exist are able to be identified on a map, whereas locations that do not match with reality are labeled ‘not provided or not identified‘. User analysis of #wddchat14 yields 271 unidentifiable locations from the 602 total participants – 45%.

It’s worth keeping that unidentified 45% in mind as we look at worldwide participation.

But if you’re anything like me, pictures speak more clearly than tables, so I pulled a map of #wddchat14 participation for the 24-hour window.

User Locations of #wddchat14 Tweets (Worldwide)
User Locations of #wddchat14 Tweets (Worldwide)

For these maps, the darker the color, the greater the participation. As you can see, the United States had the most identifiable participants – 26.2% of users. To that end, here’s a map of participation during the same 24-hour window, for participants within the United States.

User Locations of #wddchat14 Tweets (US Only)
User Locations of #wddchat14 Tweets (US Only)

To show how these tweets appeared on an hourly basis, I’ve created an animated .gif of the participation map. Each frame represents an hour-long portion of the #wddchat14 chat, starting at midnight.

User Locations of #wddchat14 Tweets (Worldwide), by Hour
User Locations of #wddchat14 Tweets (Worldwide), by Hour

And for the United States.

User Locations of #wddchat14 Tweets (US Only), by Hour
User Locations of #wddchat14 Tweets (US Only), by Hour

Matching the changing demographics of participation with the number of Tweets each hour illustrates the extent of each country’s participation.

Tweet Activity, by Hour, of #wddchat14
Tweet Activity, by Hour, of #wddchat14

Finally, I wanted to look at the potential of a worldwide diabetes chat. While it’s difficult to measure the entire worldwide conversation around diabetes in a timely manner, for the sake of simplicity, I will show the potential of #wddchat14 by looking at worldwide use of #diabetes during the same 24-hour period.

Comparison of #wddchat14 and #diabetes usage (Worldwide)
Comparison of #wddchat14 and #diabetes usage (Worldwide)

To fill in the map, #wddchat14 was identified in 6,709 tweets from 602 users while #diabetes was used in 26,763 tweets from 16,064 users.


How might we leverage the potential of the worldwide conversation about diabetes to create a truly worldwide diabetes chat? How might we embrace the diversity of the online diabetes population for community efforts like this chat? What would it take to truly get the world’s participation in world diabetes day?

Christopher Snider

Christopher Snider - @iam_spartacus

As the Patient Community Advocate at Symplur, Christopher is responsible for bringing data to the patients. He believes in the power of storytelling, that the stories we share strengthen patient communities, and that every story is worth telling no matter how ordinary it may appear to be on the surface.

What do you get when you combine the world's largest database of social healthcare conversations with the world's largest database of healthcare influencers and power it all by machine learning?

The most fun and effortless path to understanding healthcare social media.

Symplur Signals is used by pharma, medical device companies, governments and research institutions.