Political Donations 2015/16

Yesterday, the ABC released a dataset detailing donations made to political parties in Australia during the 2015-16 period. You can find their analysis and the data here. The data itself isn’t a particularly good representation of what was happening during the period: there isn’t a single donation to the One Nation Party among the lot of them, for example. This data isn’t a complete picture of what’s going on.

While the ABC made a pretty valiant effort to categorise where the donations were coming from, “uncategorised” was the last resort for many of the donors.

Who gets the money?

In total, there were 49 unique groups who received the money. Many of these were state branches of national parties, for example the Liberal Party of Australia – ACT Division, Liberal Party of Australia (S.A. Division) and so on. I’ve grouped these and others like it together under their national party. Other groups included small narrowly-focussed parties like the Shooters, Fishers and Farmers Party and the Australian Sex Party. Small micro parties like the Jacqui Lambie Network, Katter’s Australian Party and so on were grouped together. Parties with a conservative focus (Australian Christians, Family First, Democratic Labor Party) were grouped and those with a progressive focus (Australian Equality Party, Socialist Alliance) were also grouped together. Parties focused on immigration were combined.

The following chart shows the value of the donation declared and the recipient group that received it.

Scatter plot

Only one individual donation exceeded $500 000 and that was to the Liberal Party. It’s obscuring the rest of the distribution, so I’ve removed it in the next chart. Both the major parties receive more donations than the other parties, which comes as no surprise to anyone. However, the Greens have a proportion of very generous givers ($100 000+) which is quite substantial. The interesting question is not so much as who received it, but who gave the money.

Scatter plot with outlier removed

 

Who gave the money?

This is probably the more interesting point. The following charts use the ABC’s categories to see if we can break down where the (declared) money trail lies (for donations $500 000 and under). Again, the data confirmed what everyone already knew: unions give to the Labor party. Finance and insurance gave heavily to the Liberal Party (among others). Several clusters stand out, though: uncategorised donors give substantially to minor parties and the Greens have two major clusters of donors: individuals and a smaller one in the agriculture category.

Donor categories and value scatter plot

Breaking this down further, if we just look at where the money came from and who it went to, we can see that the immigration-focused parties are powered almost entirely by individual donations with some from uncategorised donors. Minor parties are powered by family trusts, unions and uncategorised donors. Greens by individuals, uncategorised and agriculture with some input from unions. What’s particularly interesting is the differences in Labor and Liberal donors. Compared to Liberal, Labor does not have donors in the tobacco industry, but also has less input by number of donations in agriculture, alcohol, advocacy/lobby groups, sports and water management. They also have fewer donations from uncategorised donors and more from unions.

Donors and Recipients Scatterplot

What did we learn?

Some of what we learned here was common knowledge: Labor doesn’t take donations from tobacco, but it does from unions. The unions don’t donate to Liberal, but advocacy and lobby groups do. The more interesting observations are focussed on the smaller parties: the cluster of agricultural donations for the Greens Party – normally LNP heartland; and the individual donations powering the parties focussed on immigration. The latter may have something to say for the money powering the far right.

 

Democracy Sausage Redux

One last time. I wanted to see if there was any interesting election day behaviour by following the hashtag for democracy sausage. As it turns out, there was. There was a peak of early-morning democratic enthusiasm with a bunch of sleepless auspol and sausage tragic posting furiously. It tapered off dramatically during the day as we were forced to contend with the reality of democracy.

For a change, I also calculated a basic sentiment score for each tweet and tracked that too. There was a large degree of variability on 30/06, but posting was very low that day. A late afternoon disappointment dip as people realised that we’d all packed up the BBQs and gone home before they got there was also evident. Julia Silge’s post on the subject was extremely helpful.

I’m teaching again this week and to start students off they’re doing basic charts in Excel. So here’s mine!

Line graph showing frequency and sentiment of hashtag

 

Late Night Democracy Sausage Surge

It’s hard-hitting electoral coverage over here at Rex. Democracy sausage is apparently more of  a late night event leading up to the election. Late night tweeting was driving the hashtag up until the close of 1 July. By the end of the day twitter had changed the #ausvotes emoji to a sausage sandwich. My personal prediction is another overnight lull and then a daytime surge on 02/07 petering off by 4pm on the day.

Time series graph of #democracysausage

 

And just for fun, who was the top Twitter advocate for the hashtag over the last three days? A user (bot?) called SausageSizzles. Some serious tweeting going on there. A steady focus on message and brand.

Bart chart

Meanwhile, as I write Antony Green on the ABC is teaching the country about sample size and variance of estimators at the early stage of counting.

The same as yesterday, check out this discussion on R Bloggers which provides a good amount of the code for doing this analysis.

Tracking Democracy Sausage

It’s a fine tradition here in Australia where every few years communities manfully attempt to make up funding gaps in the selling and eating of #democracysausage to the captured audience of compulsory voters.

For fun, I decided to see if we could track the interest in the hashtag on twitter over time. I’ve exported the frequencies out to excel for this graph making exercise, because I’ll be teaching a class on stats entirely in excel in a few weeks and this will make for some fun discussion.

Democracy sausage line graph

As we can see, as of last night (2 more sleeps until #democracysausage day), interest on twitter was increasing. I’ll bring you a democracy sausage update tomorrow.

Technical notes: the API I’m using would only pull a maximum of 350 tweets featuring the hashtag on any given day: I suspect we may be missing some interest in sausages. I’ll look into other ways of doing this.

One very useful resource formed the bulk of the programming required: this blog post on R bloggers takes you through the basics required to do the same to any hashtag you may be interested in exploring.

Happy democracy sausage day!

What if policies have networks like people?

It’s been policy-light this election season, but some policy areas are up for debate. Others are being carefully avoided by mutual agreement, much like at Christmas lunch when we all tacitly agree we aren’t bringing up What Aunty Betty Did Last Year After Twelve Sherries. It’s all too painful, we’ll never come to any kind of agreement and we should just pretend like it’s not important.

However, policy doesn’t happen in a vacuum and I wondered if it was possible that using a social network-type analysis might illustrate something about the policy debate that is occurring during this election season.

To test the theory, I used the transcripts of the campaign launch speeches of Malcolm Turnbull and Bill Shorten. These are interesting documents to examine, because they are at one and the same time an affirmation of each parties’ policy aspirations for the campaign as well as a rejection of the other’s. I used a simple social network analysis, similar to that used in the Aeneid study. If you want to try it yourself, you can find the R script here.

Deciding on the topics to examine was some trial and error, but the list was eventually narrowed down to 19 topics that have been the themes of the election year: jobs, growth, housing, childcare, superannuation, health, education, borders, immigration, tax, medicare, climate change,marriage equality, offshore processing, environment, boats, asylum, business and bulk billing. These aren’t the topics that the parties necessarily want to talk about, but they are nonetheless being talked about.

It took some manoeuvring to get a network that was readable, but one layout (Kamada Kawaii for the interested) stood out. I think it describes the policy state quite well, visually speaking.

topic network 160627

We have the inner circle of high disagreement: borders, environment, superannuation, boats and immigration. There is a middle circle doing the job of containment: jobs and growth, housing, childcare, education, medicare, business and tax- all standard election fodder.

Then we have the outer arc of topics neither the labor or liberal parties really wants to engage with: offshore processing, asylum (as opposed to immigration, boats and borders), climate change (much more difficult to manage than mere environment), bulk billing (the crux of medicare) and marriage equality (have a plebiscite, have a free parliamentary vote, have something, except responsibility). I found it interesting that the two leaders’ speeches when visualised contain one part of a policy debate around immigration: boats and borders. But they conspicuously avoided discussing the unpleasant details: offshore processing.

Much like Aunty Betty and her unfortunate incident with the cold ham, both parties are in tacit agreement to ignore the difficult parts of a policy debate.

Australia Votes: Only Six Days to Go

It’s been painful, frankly pretty lame on the policy front and we’re over it. We all go to the national quadrennial BBQ election next week. While we’re standing in line clutching our sausage sandwiches and/or delightful local baked goods, it’d be nice to have an idea of what the people we’re voting for have had to say.

So another word cloud it is, because neither side has dared offer a policy that might stray from the narrative that “we’re all good blokes, really”.

This time, I requested up to 20 tweets from Turnbull and Shorten to see what’s been going on in the last couple of weeks. I got 18 back from both. Shorten (in red, below) has been talking about voting (surprise!), been screaming about medicare and apparently has an intense interest in trades with mentions of “brick” and “nails”. I hope that’s real tradies he’s talking about. Standard pollie speak “government”, “people”, “liberals”, “Turnbull” made it into the word cloud. Marriage equality also figured in the discussion.

Screen Shot 2016-06-25 at 10.18.46 PM

Turnbull (below, blue) was making a point about his relationship with the Australian muslim community, mentioning the Kirribilli house iftar and multifaith Australia. Standard coalition topics such as “investment”, “stable leaders”, “plan”, “economic”, “jobs” were all present. The AMP issue I touched on briefly last time. He appears to be trying to avoid the subject of marriage equality as much as possible.

Screen Shot 2016-06-25 at 10.19.02 PM

So there we have it: jobs and growth, the promise of stability, an Iftar in Kirribilli, marriage equality and a fascination with how we define a real or a fake tradie. If we all keep smiling fixedly, maybe we can forget about Brexit.

Q&A vs the Leaders’ Debate: is everyone singing from the same song sheet?

The election campaign is in full swing here in Australia and earlier this week the leaders of the two main parties, Malcolm Turnbull and Bill Shorten, faced off in a heavily scripted debate in which few questions were answered and the talking points were well practiced. An encounter described as “diabolical” and “boring“, fewer Australians tuned in compared to recent years. Possibly this was because they expected to hear what they had already heard before.

Since the song sheet was well rehearsed, this seemed like the perfect opportunity for another auspol word cloud. The transcript of the debate was made available on Malcolm Turnbull’s website and it was an easy enough matter of poking around and seeing what could be found. Chris Ullmann, who moderator, was added to the stop words list as he was a prominent feature in earlier versions of the cloud.

debate word cloud

The song sheet was mild: the future tense “will” was in the middle with Shorten, labor, plan, people and Turnbull. Also featured were tax, economic, growth, change and other economic nouns like billion, (per)cent, economy, budget, superannuation. There was mention of climate, (people) smugglers, fair and action, but these were relatively isolated as topics.

In summary, this word cloud is not that different to that generated from the carefully strategised twitter feeds of Turnbull and Shorten I looked at last week.

The ABC’s program Q and A could be a better opportunity for politicians to depart from the song sheet and offer less scripted insight: why not see what the word cloud throws up?

This week’s program aired the day after the leader’s debate and featured Steve Ciobo (Liberal: minister for trade), Terri Butler (Labor: shadow parliamentary secretary for child safety and prevention of family violence), Richard di Natale (Greens, leader, his twitter word cloud is here), Nick Xenophon (independent senator) and Jacqui Lambie (independent senator).  Tony Jones hosted the program and suffered the same fate as Chris Uhlmann.

QandA word cloud

The word cloud picked up on the discursive format of the show: names of panellists feature prominently. Interestingly, Richard di Natale appears in the centre. Also prominent are election related words such as Australia, government, country, question, debate.

Looking at other topics thrown up by the word cloud, there is a broad range: penalty rates, coal, senate, economy, businesses, greens, policy, money, Queensland, medicare, politician, commission.

Two different formats, two different panels and two different sets of topics. Personally, I prefer it when the song sheet has a few more pages.

More word clouds: Auspol

Whilst I love text mining a classic work of western literature, this time I decided to stay in the present century with the twitter feeds of the leaders of the three major parties heading into a downunder federal election.

Turnbull word cloud

Malcolm Turnbull is the prime minister and leads the liberal party, he’s in blue. Bill Shorten is the opposition leader and head of the labor party, he’s in red. Richard di Natale is the leader of the Greens party, he’s in green because I had no choice there.

The outcomes are pretty interesting: apparently AMP was A.Big.Deal. lately. “Jobs” and “growth” were the other words playing on repeat for the two major parties.
Shorten Word Cloud

Each one has a distinct pattern, however. Turnbull is talking about AMP, plans, jobs, future, growth. Shorten is talking about labor, AMP, medicare, budget, schools and jobs. Di Natale is talking about the Greens, AMP (again), electricity, and auspol itself. Unlike the others, Di Natale was also particularly interested in farmers, warming and science.Word cloud Di Natale

The programming and associated sources are pretty much the same as for the Aeneid word cloud, except I used the excellent twitteR package you can find out about here. This tutorial on R Data mining was the basis of the project. The size of the corpi (that would be the plural of corpus, if you speak Latin) presented a problem and these resources here and here were particularly helpful.

For reference, I pulled the tweets from the leaders’ timelines on the evening of the 23/05/16. The same code gave me 83 tweets from Bill Shorten, 59 from Malcolm Turnbull and 33 from Richard Di Natale: all leaders are furious tweeters, so if anyone has any thoughts on why twitteR responded like that, I’d be grateful to hear.

The minimum frequencies for entering the word clouds were 3 per word for Shorten with a greater number of tweets picked up, but only 2 for Di Natale and Turnbull, due to the smaller number of available words.

I’ll try this again later in the campaign and see what turns up.