The previous exercise on users around a specific topic gave us interesting results where a certain user, such as Vogue Paris, was a dominating account in influence and control, and, being a central account, scored high on all measures. The influence of the account was validated by seeing it has close to a million followers. On the other hand, other accounts had variance in their rankings, some being central in the overall graph, and others acting as bridges, due to their content variety or being more influential due to connections with higher weight. This shows how centrality measures can be used to perform network analysis and find influential nodes on a graph network. We have used Pinterest for this analysis but centrality could be applied to multiple social networks to compute the influence of users based on various factors. A very popular tool for measuring your social influence, Klout, is an interesting example of influence analysis from social media data. However, influence scores derived from such services should be used with caution, as it is strictly limited to interactions in the digital space and not a measure of influence in real life. Aa an analogy, great leaders such Mahatma Gandhi or Nelson Mandela, never used social media but were certainly more influential than today's social media influencers!