• Soodabeh Milanlouei

Mega-donors: Who Fuelled Donald Trump's White House Run

Fall semester is coming to an end! What a year it was! The new research project that I'm involved in is overwhelmingly exciting and in a very short time period I learned so much! Besides, I had the data visualization for networks class in which I got familiar with new concepts in this area. We mainly used D3 in JavaScript to create interactive visualization. Having zero knowledge in JavaScript, I found it pretty challenging learning D3! Anyhow,me and Reyhaneh, my teammate, worked on the final project together and survived the class!

I'd like to show a small part of our project here. Even though it's not an astonishing work, we are still proud of ourselves learning a bit of D3! Let me start with a short introduction.


The 2017 Presidential election was an unprecedented event in the US political history in various ways. The first female nominee passed the primaries and made it to the general election, the amount of money raised by the political campaigns broke a record, and a nominee with no prior political experience made it to the White House. Among possible drivers for the election outcome, the monetary contribution to the presidential campaigns has had an indisputable role.

Hillary Clinton's and Donald Trump's campaigns raised 184 million dollars overall [1], setting a new record in the US presidential campaigning history. Tracing the footprints of money going to Trump's related campaigns would enable us to analyze the influence of key players - referred to as mega-donors - on Trump's success in his run for the White House.

After the Watergate scandal in 1974, the US Congress passed a law to increase the transparency of financial activities in the political system, indicating that each campaign contribution over a certain amount should be declared to the Federal Election Commission (FEC) [2]. The FEC data is now publicly available for transactions which exceed $200 which makes it easier to detect cases of fraud. There is a disambiguated version of the official release of the campaign contributions database by Navid Dianati which is available in [3]. We chose this database to study the monetary network around Trump. Initially, we filtered the committees which were closely related to the Donald Trump presidential campaign in 2016. Among all donors to the filtered committees, the mega-donors were kept while defining a threshold for the total transaction amount equal to $300,000. Then, we tracked these mega-donors back until 1992 to see their past behavior. In this way, new committees were introduced to the picture.

The overall view of the visualization


Our visualization has four views: bipartite view, time-varying bipartite view, projected view, and map view (figure above). Here, I'm only showing the bipartite view. The bipartite network is a nice way to show relations among two distinct groups of nodes which do not have any connections among themselves. In our case, there is a potential one-way relation between a pair of donor-committee and there is no direct apparent interaction among donors or among committees. The bipartite view comes in two formats: aggregated and time-dependent. In both formats, a set of nodes (red) refers to committees placed at the bottom and the other set refers to donors (orange) placed on the top. In the aggregated mode, transactions for each donor-committee pair is computed and shown on a network in which the size of node resembles the amount of money a donor (committee) contributed (received). Also, the edge thickness shows the amount of total transaction between two endpoints.

There are three options to interact with the visualization. By hovering over a node additional information such as name and photo for donors and description for committees will be displayed. By clicking on a node, the connected links and neighbors are highlighted, enabling us to go over its neighbors and links and get more information. Moreover, hovering on a link shows the amount of transaction associated with that link. Below, you can see the bipartite view.

What We Learned From the Data

The bipartite view shows that Geoffrey Palmer, Phil Ruffin, and Donald Trump himself are topping the list of mega-donors. Born into wealth, Palmer started his business in the real estate at a young age. He donated $2 million to the Rebuilding America Now PAC, making him the single top donor to this PAC. Palmer never responded to questions asking about his reason to donate to Trump and it is not clear whether the two are friends [4]. On the other hand, Phil Ruffin, billionaire Las Vegas casino owner, is a business partner also a social friend of Trump's. Donating $2 million to the Make America Great Again PAC made him the biggest donor to this committee. He also donated $1 million to Trumps's inauguration committee [5]. Despite Ruffin's close association with the Republican Party, his historical data reveals donations to Barack Obama's presidential campaign, John Kerry's senate and presidential campaigns, and Nevada (his residential state) and Kansas Democrat Party committees. After all, Donald Trump also put to use his own cash, beside the assets and infrastructures of his business which makes him the biggest donor to his own cause [6]. He solely donated $2.5 million to the Donald J. Trump for President INC committee.

Looking over the occupation of the mega-donors reveals that most of the mega-donors are usually CEOs, real estate owners, or bankers. However, there are some cases in which the occupation has been specified as homemaker. In fact, it turned out due to the regulations on the maximum amount of the political contributions, some donors decided to transfer the money under their spouse's name who have homemaker as occupation.

The map view shows that California, New York, Texas, Florida, and Illinois are the leading states in raising money for the Republican nominee. However, in the general election, Trump lost to Clinton in California, New York, and Illinois. Moreover, Clinton raised more money in general than Trump during the 2016 presidential race ($1.2 billion for Clinton and $650 million for Trump). This prompted us to look into the historical data to see whether winning in the fund-raising race has ever made a difference to the US election results. According to figures in Germany's Handelsblatt newspaper, all of the election winners in recent years were also budget winners. In both 2008 and 2012 presidential elections, Obama raised more money than Romney McCain and Romney, taking the White House in both occasions. George W. Bush also won the presidential race in 2000 and 2004, having raised more money than Al Gore and John Kerry. In the 1992 and 1996, Bill Clinton had shown the same pattern. This trend goes back until Jimmy Carter's win in 1976. Even though there seems to be a strong correlation between the budget winning and election winning, Donald Trump has broken the chain and become the first budget loser to own the White House since 1976 [7].

So, that was it! If you find data visualization interesting, start learning D3 not tomorrow but today! I'm gonna end this post by a quote from Henry D. Hubbard: There is a magic in graphs. The profile of a curve reveals in a flash a whole situation — the life history of an epidemic, a panic, or an era of prosperity. The curve informs the mind, awakens the imagination, convinces.

[1] Brittany Harris Bill Allison Mira Rojanasakul and Cedric Sam. CTracking the 2016 Presidential Money Race. 2016. URL: (visited on 12/05/2017).

[2] Bradley A Smith and Stephen M Hoersting. “A toothless Anaconda: innovation, impotence and overenforcement at the federal election commission”. In: Election Law Journal 1.2 (2002), pp. 145–171.

[3] Navid Dianati. Disambiguated FEC campaign contribution database. 2016. DOI: 10. 7910/DVN/BQN6XE. URL: http://dx.doi. org/10.7910/DVN/BQN6XE.

[4] Matt Tinoco. Trump’s Los Angeles Money Man. 2016. URL: (visited on 12/07/2017).

[5] Al Drago. The Other Trump Scandal Hiding in Plain Sight. 2017. URL: https :// (visited on 12/07/2017).

[6] Brittany Harris Bill Allison Mira Rojanasakul and Cedric Sam. CTracking the 2016 Presidential Money Race. 2016. URL: (visited on 12/05/2017).

[7] Niall McCarthy. How Much Does Money Matter In U.S. Presidential Elections? 2016. URL: #53e2988a6a6a (visited on 12/09/2017).

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