I recently made a change to the Scottish Parliament parser in ukparse so that it would preserve as accurately as possible where the timestamps occur within the text of the Official Report. (These are now in <placeholder> tags throughout the XML.) One of the things this lets us do is get a rough estimate of how fast each MSP talks. This isn’t meant to be taken particularly seriously, for the various reason given below, but it’s perhaps a nice example of how you can use the structured data version of Scottish Parliament that I created for They Work For You Scotland for simple analyses of what’s being said in parliament.
Top 25 Fastest-Talking MSPs
This league table was very quickly put together, so I apologise for any errors – it’s only really meant as a demonstration anyway. I’ve only included the top 25, since the slower end of the table tends to be distorted by non-speech actions in the parliament falling in between timestamps and appearing to make a speech slower than it actually was. On the other hand, there is no converse effect (speeches appearing to be faster than they were) that can arise except through errors in the timestamps in the Official Report.
It’s worth noting that since speeches are typically time-limited by the Presiding Officer, there is a incentive to talk fast. Also the variance in words-per-minute in this top 25 is not large, and having watched videos of these MSPs’ speeches, it’s clear that that there isn’t an obvious relationship between clarity and average words-per-minute.
| Rank | MSP | Words Per Minute | Total Words | Total Time (Minutes) | Measured Passages |
|---|---|---|---|---|---|
| 1 | Christina McKelvie | 188.5 | 11501 | 61 | 14 |
| 2 | Jackson Carlaw | 180.8 | 23139 | 128 | 24 |
| 3 | Keith Brown | 178.0 | 17622 | 99 | 20 |
| 4 | Aileen Campbell | 176.7 | 22617 | 128 | 23 |
| 5 | Liam McArthur | 176.6 | 28437 | 161 | 33 |
| 6 | Kenneth Macintosh | 176.4 | 49403 | 280 | 58 |
| 7 | Alison McInnes | 176.1 | 15500 | 88 | 18 |
| 8 | Bill Wilson | 175.6 | 14929 | 85 | 17 |
| 9 | David Whitton | 175.5 | 22813 | 130 | 27 |
| 10 | Richard Baker | 174.2 | 33619 | 193 | 49 |
| 11 | Anne McLaughlin | 173.3 | 3812 | 22 | 4 |
| 12 | Iain Smith | 173.2 | 56111 | 324 | 64 |
| 13 | Peter Peacock | 172.3 | 31702 | 184 | 38 |
| 14 | Richard Lochhead | 171.9 | 64458 | 375 | 77 |
| 15 | Stewart Maxwell | 171.3 | 41454 | 242 | 44 |
| 16 | Claire Baker | 170.6 | 13477 | 79 | 15 |
| 17 | Alasdair Allan | 169.5 | 15594 | 92 | 18 |
| 18 | Eleanor Scott | 169.1 | 63076 | 373 | 88 |
| 19 | Johann Lamont | 169.1 | 75237 | 445 | 84 |
| 20 | Alasdair Morrison | 168.9 | 22628 | 134 | 26 |
| 21 | Mike Watson | 168.6 | 16019 | 95 | 23 |
| 22 | Sarah Boyack | 168.1 | 72778 | 433 | 70 |
| 23 | Kenneth Gibson | 167.5 | 62293 | 372 | 77 |
| 24 | Andrew Wilson | 167.2 | 5351 | 32 | 9 |
| 25 | Nanette Milne | 167.0 | 77828 | 466 | 101 |
More Details
You can find the fastest-msps.py script in the ukparse repository as usual.
The script only takes notice of a speech when there is a single speaker between two consecutive timepoints. Unfortunately, this doesn’t happen as often as I would like, so you only get a small sample of each MSP’s speeches represented here – another reason to be suspicious of the results.
The script ignores timestamps that have the same time as the previous one and any speeches that contain text like “meeting suspended”, which often indicate that the next timestamp falls at the end of the break in proceedings. It also ignores any speech less than 2 minutes in length, since these have the highest error. “Words” are just considered to be anything in the speech that’s separated by whitespace.
I’ve also excluded the following speakers:
- Anyone who has spoken in the Official Report who isn’t an MSP, such as Her Majesty the Queen and the speakers at Time for Reflection.
- Anyone who has presided over the parliament, in particular the Presiding Officer and Deputy Presiding Officers. Whoever is chairing proceedings often has to introduce breaks, divisions or other actions which have no reported speech attached to them but nonetheless take up time between the placeholders, so their apparent speaking speed is much too low.
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