{"id":1165,"date":"2010-08-17T16:45:18","date_gmt":"2010-08-17T06:45:18","guid":{"rendered":"http:\/\/www.mappingonlinepublics.net\/2010\/08\/17\/twitters-response-to-gillard-and-abbott-on-qa\/"},"modified":"2012-04-10T14:21:41","modified_gmt":"2012-04-10T04:21:41","slug":"twitters-response-to-gillard-and-abbott-on-qa-2","status":"publish","type":"post","link":"https:\/\/mappingonlinepublics.net\/dev\/2010\/08\/17\/twitters-response-to-gillard-and-abbott-on-qa-2\/","title":{"rendered":"Twitter\u2019s Response to Gillard (and Abbott) on Q&A"},"content":{"rendered":"

By popular demand<\/a>, here\u2019s part one of a first quick take on how Australia\u2019s major political leaders fared with their appearances on the ABC\u2019s Q&A<\/a><\/em> programme, in the eyes of the (surprisingly massive) Twitter<\/em> audience that Q&A<\/em> manages to generate \u2013 for both of their appearances this week (Tony Abbott<\/a>) and last (Julia Gillard<\/a>), the #qanda hashtag became a globally trending topic.<\/p>\n

Let\u2019s begin with some baseline data (provided, once again, by Twapperkeeper<\/a><\/em>): here\u2019s the total amount of tweets before, during, and after the screening of Q&A<\/em> on ABC1, hour by hour.<\/p>\n

<\/p>\n

\"image\"<\/a> <\/p>\n

Some staggering numbers there \u2013 between 10 and 11 p.m. on Tuesday (i.e. during the second half of the programme, which starts around 9.30 p.m. AEST), both leaders comfortably beat the 10,000 tweets\/hour mark. Also notable: there\u2019s no significant blip a few hours later, when Q&A<\/em> is screened again at 9.30 p.m. in Western Australia \u2013 so perhaps those WA viewers who are given to tweeting along with Q&A<\/em> watch the programme\u2019s online live stream rather than the time-delayed TV broadcast.<\/p>\n

Before we get too excited about Gillard appearing to generate significantly more tweets than Abbott: a closer look at the data reveals some problems with the Twapperkeeper<\/em> dataset from last night (and I\u2019ve submitted a request to re-capture those #qanda tweets \u2013 it\u2019s quite possible that they\u2019re still simply too fresh to have been processed). Here\u2019s the minute-by minute comparison of tweeting activity between 9 p.m. and 12 a.m. on each of the two Monday nights:<\/p>\n

\"image\"<\/a> <\/p>\n<\/p>\n

You\u2019ll note that there are several periods of time (the longest between 22:18 and 22:27) when the Tony Abbott tweetstream simply flatlines. Now, anybody who was watching Twitter<\/em> during Q&A<\/em> last night would know that there were no such periods of total inactivity at any point \u2013 so clearly, there\u2019s a problem with the data for the Abbott Q&A<\/em>. What\u2019s also obvious: during the periods where we do<\/em> have reliable data, the volume of tweets on Abbott\u2019s night is consistently above the volume on Gillard\u2019s night. So, my guess is that with the gaps filled in, we would see significantly more tweets responding to Abbott than we did for Gillard \u2013 where during the programme, Gillard averages probably around 360 tweets per minute, Abbott looks to be closer to 530 tweets per minute. <\/p>\n

(And that would also align with my observation that during the past week, Abbott was mentioned more often than Gillard in tweets using the general #ausvotes hashtag<\/a>.)<\/p>\n

But let\u2019s have a look at the content. Following the same methodology as I\u2019ve outlined here<\/a>, here\u2019s a list of the top keywords for the tweets during 9 p.m. and midnight on Gillard\u2019s night:<\/p>\n

\"image\"<\/a> <\/p>\n

(I\u2019ve removed some of the more obvious or meaningless keywords from this list: Abbott, answer, Australia, big, didn\u2019t, doesn\u2019t, election, Gillard, good, great, hear, isn\u2019t, JG, Julia, juliagillard, [I\u2019\/we\u2019]ll, make, Mark, Mr, people, PM, qanda, question, real, show, thing, time, tonight, Tony, tweet, [I\u2019\/we\u2019]ve, watch, and week.)<\/p>\n<\/p>\n

And the key phrases come in like this:<\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
 <\/td>\nFREQUENCY<\/td>\n<\/tr>\n
JULIA GILLARD<\/td>\n811<\/td>\n<\/tr>\n
MENTAL HEALTH<\/td>\n636<\/td>\n<\/tr>\n
TONY ABBOTT<\/td>\n392<\/td>\n<\/tr>\n
SEX MARRIAGE<\/td>\n342<\/td>\n<\/tr>\n
CLIMATE CHANGE<\/td>\n330<\/td>\n<\/tr>\n
MARK LATHAM<\/td>\n307<\/td>\n<\/tr>\n
REAL JULIA<\/td>\n291<\/td>\n<\/tr>\n
QANDA TONIGHT<\/td>\n284<\/td>\n<\/tr>\n
TONY JONES<\/td>\n236<\/td>\n<\/tr>\n
GOOD QUESTION<\/td>\n224<\/td>\n<\/tr>\n
MR RABBIT<\/td>\n224<\/td>\n<\/tr>\n
MOVE FORWARD<\/td>\n222<\/td>\n<\/tr>\n
GAY MARRIAGE<\/td>\n214<\/td>\n<\/tr>\n
PRIME MINISTER<\/td>\n209<\/td>\n<\/tr>\n
BOAT PEOPLE<\/td>\n207<\/td>\n<\/tr>\n
QANDA JULIA<\/td>\n185<\/td>\n<\/tr>\n
INTERNET FILTER<\/td>\n159<\/td>\n<\/tr>\n
NET FILTER<\/td>\n147<\/td>\n<\/tr>\n
ASYLUM SEEKER<\/td>\n139<\/td>\n<\/tr>\n
ANSWER THE QUESTION<\/td>\n133<\/td>\n<\/tr>\n
JOHN HOWARD<\/td>\n131<\/td>\n<\/tr>\n
TOOL IS MARK LATHAM<\/td>\n121<\/td>\n<\/tr>\n
QANDA AUDIENCE<\/td>\n120<\/td>\n<\/tr>\n
MENTAL HEALTH IS A SECOND TERM ITEM<\/td>\n109<\/td>\n<\/tr>\n
MILLION FOR A NET FILTER THAT WON<\/td>\n107<\/td>\n<\/tr>\n
WORK BUT MENTAL HEALTH<\/td>\n107<\/td>\n<\/tr>\n
MENTAL HEALTH FUND<\/td>\n107<\/td>\n<\/tr>\n
CITIZEN ASSEMBLY<\/td>\n96<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

No surprise, of course, to see Gillard and Abbott themselves mentioned frequently, as well as Q&A<\/em> host Tony Jones and former Labor leader turned serial pest Mark Latham – subject especially of the following much-tweeted question-and-answer exchange:<\/p>\n

\n

‘How big a tool is Mark Latham?’ ‘There are some things that can’t be measured?’ #qanda<\/p>\n<\/blockquote>\n

There are also the obvious comments about the then newly-unveiled \u2018Real Julia\u2019, her pronunciation of Tony Abbott as \u2018Mr Rabbit\u2019, and the discredited slogan \u2018moving forward\u2019 \u2013 however, it is evident that actual political and policy issues also rate highly.<\/p>\n

Here, comments on Labor\u2019s mental health policy are most prevalent (636 mentions); however, almost 100 of those mentions are from retweets of Chaser<\/em> star Chas Licciardello\u2019s line <\/p>\n

\n

RT @ChasLicc: I would have thought Gillard would be more open to mental health funding after the Latham episode #qanda<\/p>\n<\/blockquote>\n

Tweets on same-sex marriage and climate change appear roughly equal in volume (342 vs. 330 mentions – but also note an addition 214 mentions for \u2018gay marriage\u2019, and 96 for the proposed \u2018citizens\u2019 assembly\u2019 to discuss climate change); on same-sex marriage, there again are some prominent re-tweets boosting the numbers, but this time they\u2019re topical rather than comical:<\/p>\n

\n

RT @dctcool: Same sex marriage should go to referendum RT If you agree #qanda<\/p>\n

RT @samesame: You’re right Julia your answer on same-sex marriage does disappoint us. #qanda<\/p>\n<\/blockquote>\n

Boat people and asylum seekers appear further down the order (207\/139 mentions), again with a number of prominent re-tweets. And again, it\u2019s the media personalities who supply the comedy:<\/p>\n

\n

RT @CatherineDeveny: What?  30 minutes in and no talk of boat people?  This is bullshit #qanda<\/p>\n

RT @safran_john: Idea for Refugee advocates: humanise boat people by calling them boat peeps. #qanda<\/p>\n<\/blockquote>\n

While others remain more serious and focus on the topic at hand:<\/p>\n

\n

RT @wolfcat: here is an idea lets just use australia to process boat people #qanda<\/p>\n<\/blockquote>\n

And of course the \u2018cleanfeed\u2019 Internet filter also appears, variously as \u2018Internet filter\u2019 (159) or \u2018Net filter\u2019 (147) \u2013 especially in the much-retweeted line <\/p>\n

\n

RT @xtensha: 40 million for a net filter that won’t work but mental health is a second term item… Get real Julia #openinternet #qanda<\/p>\n<\/blockquote>\n

(Note that the bottom few lines of the table above are all subsets of the same retweet; WordStat can only capture phrases consisting of up to 7 words, so it chopped up that tweet in a number of different ways.)<\/p>\n

And finally for a map of those keywords as they occur together (and those co-occurrences are necessarily skewed in favour of the most heavily retweeted phrases, of course \u2013 hence the conflation of mental health, the Internet filter, and Mark Latham into a cluster in the upper left corner):<\/p>\n