Identifying subgroups within your network
You must write a blog post of 750 words about your data set. The following three parts will be assessed and must be addressed. You should support your responses with reference to existing literature where appropriate.
Identify any significant subgroups within your network using as many measures as are appropriate for your data (e.g. clustering coefficient, and assessment of cliques, and the Girvan-Newman algorithm). Girvan-Newman Bear in mind that all of these measures might not be appropriate for your network, or yield fruitful results. It is up to you to decide what measures to use with your data – and whether any emergent subgroups actually make sense.
Provide commentary on the implications of your findings. In what ways might these subgroups contribute to overall network outcomes in the context of your network? In the event that no subgroups emerge – why do you think this might be significant?
Generate a network map of your network using Net Draw that clearly identifies any important subgroups you find. You can do this by adjusting or creating node attributes (i.e. an attribute dataset) and thus changing node colours, shapes, or sizes where appropriate. You should refer to these nodes in the body of your blog post text, and upload the jpeg file as an attachment to your blog post.
NOTE: Be mindful of any limitations of your own data that might preclude a specific type of analysis.
ALSO NOTE: Do not attach your reference list as an additional attachment. It should be included in the body of your blog post (it will not count towards your word limit).
