Analysing Social Media Collaboration

Analysing Social Media Collaboration

Analysing Social Media Collaboration.  Are a multidisciplinary group of researchers interested in analysing data from social media such as Twitter with the aim to understand the role they play in social phenomena. While there are high profile cases where social media have played a very visible role, e.g., during the Summer riots in England in 2011, they also play a more mundane role in the lives of many who collectively organise, share information, campaign, comment, …

We draw on the expertise of a wide range of disciplines within the social sciences that we combine with expertise in computer science. This combination allows us to exploit the rich data sources and data manipulation methods available today while drawing on the rich understanding of social phenomena provided by the social sciences. We believe that the excitement about new analytical methods enabled by pervasive computerisation needs to be married with the conceptual, theoretical and methodological achievements of different social science disciplines.

 
If you would like to know more or are interested in getting involved, contact Rob Procter (rob.procter@warwick.ac.uk).

A Few More Thoughts on the Forensic Analysis of Twitter Friend and Follower Timelines in a MOOCalytics Context

Tony Hirst's avatarouseful.info, the blog...

Immediately after posting Evaluating Event Impact Through Social Media Follower Histories, With Possible Relevance to cMOOC Learning Analytics, I took the dog out for a walk to ponder the practicalities of constructing follower (or friend) acquisition charts for accounts with only a low number of followers, or friends, as might be the case for folk taking a MOOC or who have attended a particular event. One aim I had in mind was to probe the extent to which a MOOC may help developing social ties between folk taking a MOOC, whether MOOC participants know each other prior taking the MOOC, or whether they come to develop social links after taking the MOOC. Another aim was simply to see whether we could identify from changes in velocity or makeup of follower acquisition curves whether particular events led either to growth in follower numbers or community development between followers.

To recap…

View original post 1,125 more words