The ranking of political influence on Twitter aims to reward excellence within our network of influencers. This ranking is based on the network of think tanks and the political analysts linked to them for whom political influence is the essence of their daily work.
The network develops a series of variables that asses and quantify the relationship between all the participating nodes; we use these variables to create a synthetic indicator that, after being conveniently weighted, helps us to design an index of political influence for the reality we are analyzing.
The index valuates the indegree (how many people are reading you) of each node in the network and its pagerank (how many people are reading you weighted by the importance of those people). It also respects the horizontal and democratic nature of the network itself, so that a high pagerank in a particular node also contributes to increase the relevance of the nodes with which it interacts.
The last variable influencing the indicator is centrality (Betweenness centrality, i. e. how many people would have to pass through you to get to any other node using the shortest path) since it helps the nodes to be more present in the network by valuing the effect of betweenness over other factors within the network.
In short, the influencers who lose the most are those who favor listening over being listened to and fail to gain importance in the betweenness of the network. That is, they have spread influence but by doing so they did not manage to increase their overall importance.