Connecting the Cosponsorship Dots
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Politics is, at its heart, about relationships. Since majority support is required to enact laws, legislators must dedicate time to building alliances with colleagues who will support their ideas and -- ultimately -- their bills. Forging connections in a legislative body isn’t just a part of an elected official’s job; it’s a critical function that shapes how the government operates.
For newcomers and outsiders, navigating these invisible relationships can be tricky. One of the steepest parts of the learning curve is knowing who is close to whom, who agrees with what, and how networks of influence are distributed. Without insider info, the task can seem impossible.
Luckily, lawmakers pull back the curtains on these relationships a bit when they sign onto legislation. By cosponsoring a bill, a legislator signals what they support (at least in theory), and with whom they agree.
We can then use that information to map out connections inside a legislature. With network analysis, we can answer questions such as:
Who sits at a central position in the chamber?
Which lawmakers are more closely connected to others?
How has a legislator’s position changed over time?
Mapping the Massachusetts State House
Network analysis is the study of social relations among a set of people by means of graph theory. It has been used to look at everything from Congress to the Seven Kingdoms and can uncover aspects of an institution that would otherwise be too difficult to parse out.
In our study, we analyzed the networks of the Massachusetts State House by examining cosponsorship data from the past twelve years. You can explore it too at https://legislata.shinyapps.io/CosponsorshipApp/#
Before jumping into the data, let’s talk about methodology.
In order to determine the strength of relationships between lawmakers, we first had to score the quality of each connection. In our model, we distinguish between bills with many cosponsors and those with only a few.
For example, an uncontroversial bill that has the support of everyone in the legislature does not tell us much about the relationship between two of the cosponsors. A bill with only two cosponsors indicates a much closer relationship or ideological/regional connection between the legislators.
Using this theory, we weighted the cosponsorships: if 100 legislators sign onto a bill, then the connection between any two of them is 1/100, or 0.01. If only 2 legislators cosponsor a bill, the connection is ½, or 0.5. We then plotted out the weighted connections between every legislator using network analysis software packages.
Once the network was mapped, we were able to identify two key metrics: centrality and betweenness.
Centrality
In our model, we identify key players in the State House by looking at their centrality score. This metric is based on a) how many connections a person has, but also b) how connected their connections are.
Here’s an example: if we were to apply this to Washington, White House Chief of Staff Ron Klain would probably have the highest centrality score since he has connections to the President, all Cabinet Members, and Congressional leadership. He sits at the center of some very important people, even if he isn’t the most important himself.
In our study, we found that centrality is somewhat related to how many cosponsorships a legislator makes. The more bills a Representative or Senator signs onto, the likelier they will end up more closely connected to everyone else; however, the quantity of cosponsorships isn’t the sole determining factor in centrality. Other factors may include ideology, personal connections, whether they have similar interests to many others, etc. While this study didn’t focus on these other aspects, they should be considered.
In our study, the most central figures in the Massachusetts State House in the last session were:
Rep. Natalie Higgins
Rep. David Rogers
Sen. Jamie Eldridge
Sen. Sal DiDomenico
Betweenness
Another metric worth exploring is a person’s “betweenness” in a given network. This metric identifies the people who connect different communities. For example, a diplomat would likely score high on “betweenness.” While individual diplomats may not have lots of connections within their own government or their host government, they act as a bridge between the two.
In our study, we found that cosponsoring legislation wasn’t especially correlated with betweenness. Rather, these “bridge” legislators are more likely to cosponsor bills with different types of people than add their names to many bills. Sen. John McCain (usually conservative but who worked on major legislation with the very liberal Senators Russ Feingold and Bernie Sanders) was an example of a highly between legislator.
In our study, the most between figures in the Massachusetts State House in the last session were:
Rep. Ted Speliotis
Rep. Aaron Michlewitz
Sen. Michael Rodrigues
Sen. Sonia Chang-Diaz
Centrality vs. Betweenness
To the small extent that centrality and betweenness are connected, they’re inversely related. More between legislators are less likely to be more central legislators, and vice versa.
Interestingly, there seems to be little correlation between tenure and either centrality or betweenness. While we might assume that legislators move into a more central position the longer they hold office, that doesn’t appear to be true — at least not in the aggregate.
So, what does the data tell us?
Cosponsorship structures provide an interesting look at the internal dynamics of an often opaque legislative system. When used correctly, cosponsorship data can shed light on legislators’ priorities, alliances, and influence.
At the same time, cosponsoring legislation is not the only way to be influential. A lawmaker may only work on a few issues and not cosponsor much else. A member of chamber leadership may not rely on cosponsorships to make their wishes known. (In fact, we had to filter out some of the top leadership because they cosponsored so little legislation that they skewed the data in this study.)
Context is critical to finding intelligent, meaningful insights. When matched with easily understandable and accurate data, it can take observations about politics from anecdote to analysis.
How does Legislata help?
Legislata is the workplace productivity tool for state legislators and their staff. In addition to tracking cosponsorships, our platform allows users to track constituent email, manage office tasks, and collaborate with peers in a single app.
With Legislata’s suite of tools, public servants can easily check their districts’ pulses, identify operational bottlenecks, and make data-driven policy decisions.
Legislata is in development. Sign up to be included in our closed beta test now, launching this summer.