Emerging Online Social Communities and Emergency Services in a Connected World

The following was a ‘joke’ abstract I wrote on Facebook (yes I know – get a life), and was inspired by a Queensland Police Service Media posting in relation to a specific incident.

When you are writing a paper I always finds it helps to write the abstract first – at least to clarify the purpose of the paper.  Obviously, you rewrite the abstract later.

This study develops a theoretical model from a comprehensive literature review to identify factors relating to the successful building of online communities. The developed theoretical model is then considered in the important context of emergency services and their extension to the online world. The theoretical model undertakes a secondary data analysis of material published in the public domain by these public service entities in light of the theoretical model. This qualitative analysis is supplemented through consideration of quantitative measures of the success of these communities through espoused key performance indicators such as number of ‘followers’, community engagement (measured as percentage of respondents sharing, liking, and commenting upon announcements), and time to resolution.

The mechanisms of success are explored through the qualitative analysis of the material and depth of comment made through publicly available social media. This study contributes to the practical understanding of public sector emergency services response in an online environment, and furthermore provides a theoretical framework for the consideration and extension of social media effectiveness in the current integrated social world.

Unfortunately QPS delete some of their posts when there is no longer a public benefit arising (e.g. they found someone they specifically named) – which makes getting some of the numbers a little more difficult.

I was reminded of this because of this call for research students at QUT:  http://networkedblogs.com/wvQqn

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.