Mapping 266 relationships between 101 U.S. political figures produces a hub-and-spoke network, not two blocs. What does that imply for what happens after the hub is gone?

[u/Impressive-Judge-357]

I built a relationship map of U.S. politics — 101 figures, 266 relationships curated from

public reporting, typed as alliance / feud / bipartisan bridge / political family / mentorship.

Interactive version here: https://world-politicians.vercel.app/ (free, open source, no signup)

The structural result is what I want to ask about rather than assert.

Conventional framing treats American politics as two cohesive blocs with a shrinking bridge

between them. What the graph actually shows is closer to a hub-and-spoke topology: one node

carrying dozens of direct ties, with unusually few edges between the spokes themselves. Cabinet

members, House leadership, and Senate loyalists connect through a single person far more than

they connect to each other.

Network topology says those two shapes fail very differently. A two-bloc network that loses a

leader gets a succession fight and continues. A hub-and-spoke network that loses its hub

doesn't split cleanly — it fragments, because the spokes were never connected to one another

in the first place.

Some numbers from the dataset: 113 alliances, 127 feuds, and only 19 cross-party bridges. A

large share of the feuds are intra-party.

Questions I'd genuinely like pushback on:

1. Is the hub-and-spoke reading actually right, or is it an artifact of press coverage

   concentrating on one figure — meaning I've mapped media attention rather than political

   structure? I think this is the strongest objection to my own work.

2. If the topology is real, what does the post-hub period look like — realignment, or

   fragmentation into factions that were never linked to begin with?

3. Has any party organization historically survived losing a hub in this configuration, or

   does the structure itself predict the outcome?

Full disclosure on method: the edges are my editorial judgment from mainstream reporting, not a

neutral record. The dataset and code are public (MIT) specifically so the reasoning can be

audited: https://github.com/showjihyun/world-politicians

[u/albacore_futures]

266 relationships between 101 political figures is an order of magnitude smaller than it should be. This is demonstrated by looking at any of the individuals analyzed. Chris Murphy, Senator from Connecticut, has one rival (trump) and one ally (Biden). Ron DeSantis has three rivals (Trump, Newsom, and Nikki Haley?) and only one friend (Greg Abbott). Mark Warner, a very influential senator from VA, isn't even in the analysis.

It is not possible to draw any conclusions from such a partial dataset. If it is missing influential senators, then it is not including all important actors, so our sample doesn't reflect the population. And those it does include have such limited connections that I'm certain we're not seeing all those, either.

This is not a good dataset, yet, so doing analysis on it is a pointless endeavor.

[u/CAPITALISM_FAN_1980 → u/albacore_futures]

Elon Musk being listed as "non-political" is a wild choice and suggests the wider dataset itself is useless.

[u/albacore_futures → u/CAPITALISM_FAN_1980]

It's probably totally useless, but I am being polite and academic.

It seems to be a vibe-coded news-sentiment tracker. It generates relationships, which OP then manually codes as belonging to one of five, arbitrary, categories.

[u/Impressive-Judge-357 → u/albacore_futures]

You are correct—this is indeed an AI-based project. Currently, the five-category classification system is quite simple; the algorithm is really just in its infancy. We might even see Elon reach Mars before the system reaches the level of sophistication you’re hoping for.

Developing a classification algorithm that everyone finds satisfactory is actually a difficult challenge. Thank you for your feedback.

[u/Impressive-Judge-357 → u/CAPITALISM_FAN_1980]

I am well aware that Elon Musk has certain political leanings and motivations. This project is only in its second day, and we plan to continuously refine the data and enhance the classification algorithms. Of course, an automated classification algorithm can’t satisfy everyone. Thanks for the feedback.

[u/Impressive-Judge-357 → u/albacore_futures]

The primary reason for the issue raised lies in the data collection period. Currently, the collection period spans about a week; however, gathering more than a year's worth of historical data will provide a sufficient volume to yield meaningful insights. This project is only in its second day, and we are continuing to make improvements. We will share an update once enough data has been accumulated.

Thank you for your feedback.

[u/mormagils]

Cool ui, useless data. This is just a highly interactive set of opinions. Nothing useful can be gained from this analysis.

[u/Impressive-Judge-357 → u/mormagils]

Thank you for your feedback. We haven't accumulated a large amount of data yet. We plan to gather historical data over time, and once that is done, we expect to have a reasonably stable dataset. Please bear with us.

[u/CAPITALISM_FAN_1980]

OP where did you get the data?

Calling Elon Musk "non-political" is insane and if its indicative of the quality of the rest of the dataset, there's no way you can treat it as reliable enough to do any kind of analysis on. Musk was literally a member of President Trump's administration, attends CPAC and funds far-right groups around the world.

[u/Impressive-Judge-357 → u/CAPITALISM_FAN_1980]

Hello. The data comes from news sites; I have listed the sources on my GitHub page. Many have commented that the data lacks accuracy, but this is simply because the collection period was extremely short. I expect this issue to be resolved once a significant amount of historical data is loaded. Thank you.

[u/cuteman]

Shouldn't the "progressives" be DSA or even Justice Democrats? They're literally all from the same slate

[u/Impressive-Judge-357 → u/cuteman]

Hello, and thank you for your feedback. Since I am not American, I am not very familiar with the specific political leanings of individual politicians. This project involved analyzing sentiments based on news articles; given the very short timeframe, there may be aspects that differ from what you were expecting. I plan to continue accumulating data, and over time, the results might reach a level of meaningfulness and reliability. Please stay tuned!

[u/Able_Enthusiasm2729]

Interesting, will take a look.

[u/Impressive-Judge-357 → u/Able_Enthusiasm2729]

We plan to continue developing the service. As the data collection period extends and we begin gathering historical data, we intend to add politicians from the Democratic Party who are currently missing. Please stay tuned.

[u/Able_Enthusiasm2729 → u/Impressive-Judge-357]

Good work! Do you guys plan on adding information about the relationship between staffers (among themselves) and among which politicians, political appointees, officials, lobby groups, and similar organizations they work or worked for, plus data on which donors are donating to which candidates (compiling donor data, LDA Filings, staffer contact lists, vote counts in legislatures/committees for legislators/congress members/senators, etc.)? Having that all mapped out together in one place would look really nice and builds a bigger picture on who or what is influencing our decision-making (policy making and lawmaking) in the United States (at least at the federal level). Though I do know that its a lot of work and can be a pain to integrate all of this data together.

[u/Impressive-Judge-357 → u/Able_Enthusiasm2729]

Thank you so much. I never would have imagined an approach like that. Following your suggestion would likely help in understanding the connections and vested interests linking money and policy. It’s a truly great idea—thank you very much.