Mhealth policy conversations in social media are generating lots of data, but what can this tell us about the actors, their networked relationships or their investment in formal policy processes?

The Moving Media  project has been exploring social network analysis of mhealth tagged tweets to better understand the informal policy networks that are developing on Twitter – but we’ve come up with some big questions about the analytical processes we’re using.

So we’d like to start a discussion about some of the challenges of doing SNA and network visualisations with this type of data, including things like:

• The types of tools that DH are using for SNA (Gephi vs Node XL)
• How to slice big data
• How to locate the data across maps
• How to automate the data scraping process
• How to share the data back with the users

We’d also like to know what you’re doing in this space and what discoveries you’ve made.

Paperboy icon, with the permission of the Artist Bradley David Santos www.bradleydavidsantos.net/works%5B/caption%5D

The concept is to be able to search for articles by institutions and find collaborators who are publishing in your searched interests. Three different potential user groups have been considered:
– Prospective students who are searching for institutions to study at
– Academics who want to find collaborators at other institutions.
– Policy and institution-makers who want to look strategically at the published record to inform decisions.

This experimental project was initated at ‘healthhack’ in Melbourne over the weekend.

What was achieved during the weekend is described on the wiki.
github.com/healthhack-melb/wiki/wiki/Paperboy
(N.B, the live demo is being updated this evening. Look at it on Tuesday morning).

Coders, Designers, Analysts want to make stuff during the un-ference and teach some others a little?