Self-binding note: lobby metrics

Things to get out of the data in this scraper of mine: for each lobby, the monthly meeting counts, degrees in the weighted multigraph, impact factor (i.e. graph degree/meetings to give an idea of productivity), most met ministers, most met departments, topics. For each ministry, meeting counts, most met lobbies, most discussed topics. For each PR agency (Who’s Lobbying had or has a list of clients for some of them), the same metrics as for lobbies. Summary dashboard: top lobbies, top lobbyists, top topics, graph visualisation, top 10 rising and falling lobbies by impact.

Things I’d like to have but aren’t sure how to implement: a metric of gatekeeper-ness for ministers, for example, how often a lobby met a more powerful minister after meeting this one, and its inverse, a metric of how many low-value meetings a minister had. I’ve already done some scripting for this, and NetworkX will happily produce most of the numbers, although the search for an ideal charting solution goes on. Generating the graph and subgraphs is computationally expensive, so I’m thinking of doing this when the data gets loaded up and storing the results, rather than doing the sums at runtime.

Where’s that Django tutorial? Unfortunately it’s 7.05 pm on Sunday and it’s looking unlikely I’ll do it this weekend…

    Leave a Reply

    Fill in your details below or click an icon to log in: Logo

    You are commenting using your account. Log Out /  Change )

    Twitter picture

    You are commenting using your Twitter account. Log Out /  Change )

    Facebook photo

    You are commenting using your Facebook account. Log Out /  Change )

    Connecting to %s

%d bloggers like this: