The Twitter collection I had and I’ve been posting about? I spent an hour or two getting Tweets. I stopped getting Tweets around the time the polls opened. (See this post and this for a more detailed methodology used for data gathering.) After that, I sorted the Tweets out to get rid of the duplicate Tweets. Then I get rid of the obviously not about Australian politics tweets based on the following keywords: glennbeck, #palin, #gop, #teaparty. The next step was to figure out from the location field where a tweet originated from. If the Tweet was not from Australia and I couldn’t figure out which city in Australia it was from, it was discarded from counting. This left 17,802 tweets total. After that, I sorted tweets based on party: Labor, Liberals/Nationals, Greens, Sex Party, Family First. For each party, I used that word, the name of the leader, prominent members of the party and the acronym they go by to get a more complete list of tweets. (Hockey = Joe Hockey = Liberal. Julia = Julia Gillard = Labor. Etc.) Then I tallied up the total of tweets from each city. I sorted the cities by electorate… and I got the following table. If you don’t see an electorate, no Tweets were identified as having come from it.
| State | Electorate | Liberal | Labor | Green | Family First | Sex Party |
| Australian Capital Territory | Canberra | 1 | 1 | 1 | 0 | 0 |
| Australian Capital Territory | Fraser | 85 | 84 | 34 | 0 | 0 |
| New South Wales | Banks | 1 | 1 | 0 | 0 | 0 |
| New South Wales | Barton | 1 | 1 | 0 | 0 | 0 |
| New South Wales | Bennelong | 0 | 1 | 0 | 0 | 0 |
| New South Wales | Bennelong | 0 | 0 | 0 | 0 | 1 |
| New South Wales | Berowra | 1 | 1 | 0 | 0 | 0 |
| New South Wales | Bradfield | 0 | 1 | 0 | 0 | 0 |
| New South Wales | Calare | 2 | 4 | 1 | 0 | 0 |
| New South Wales | Chifley | 66 | 121 | 7 | 0 | 0 |
| New South Wales | Cowper | 1 | 1 | 4 | 0 | 0 |
| New South Wales | Cunningham | 6 | 6 | 1 | 0 | 0 |
| New South Wales | Dobell | 1 | 1 | 0 | 0 | 0 |
| New South Wales | Eden-Monaro | 1 | 1 | 0 | 0 | 0 |
| New South Wales | Gilmore | 7 | 2 | 0 | 0 | 0 |
| New South Wales | Grayndler | 7 | 3 | 1 | 0 | 0 |
| New South Wales | Greenway | 2 | 0 | 0 | 0 | 0 |
| New South Wales | Hume | 1 | 2 | 2 | 0 | 1 |
| New South Wales | Hunter | 1 | 0 | 0 | 0 | 0 |
| New South Wales | Kingsford Smith | 0 | 1 | 1 | 0 | 1 |
| New South Wales | Lindsay | 2 | 1 | 3 | 0 | 0 |
| New South Wales | Lyne | 6 | 17 | 3 | 0 | 0 |
| New South Wales | Mackellar | 27 | 85 | 4 | 0 | 0 |
| New South Wales | Macquarie | 2 | 1 | 0 | 0 | 0 |
| New South Wales | Mitchell | 1 | 1 | 0 | 0 | 0 |
| New South Wales | New England | 5 | 6 | 4 | 0 | 2 |
| New South Wales | Newcastle | 60 | 124 | 27 | 1 | 1 |
| New South Wales | North Sydney | 13 | 47 | 1 | 0 | 0 |
| New South Wales | Paterson | 17 | 36 | 2 | 0 | 0 |
| New South Wales | Reid | 3 | 3 | 3 | 0 | 0 |
| New South Wales | Richmond | 3 | 0 | 2 | 0 | 0 |
| New South Wales | Riverina | 0 | 0 | 1 | 0 | 0 |
| New South Wales | Robertson | 3 | 10 | 1 | 0 | 0 |
| New South Wales | Sydney | 343 | 405 | 75 | 4 | 6 |
| New South Wales | Throsby | 1 | 2 | 0 | 0 | 0 |
| New South Wales | Wannon | 3 | 2 | 0 | 0 | 0 |
| New South Wales | Wentworth | 2 | 4 | 0 | 0 | 0 |
| New South Wales | Wills | 1 | 1 | 0 | 0 | 0 |
| Northern Territory | Lingiari | 1 | 1 | 1 | 0 | 0 |
| Northern Territory | Solomon | 1 | 4 | 0 | 0 | 0 |
| Queensland | Blair | 0 | 1 | 0 | 0 | 0 |
| Queensland | Brisbane | 97 | 115 | 20 | 1 | 5 |
| Queensland | Capricornia | 1 | 1 | 0 | 0 | 0 |
| Queensland | Dawson | 3 | 9 | 2 | 0 | 0 |
| Queensland | Fairfax | 1 | 1 | 0 | 0 | 0 |
| Queensland | Flynn | 1 | 1 | 0 | 0 | 0 |
| Queensland | Griffith | 1 | 1 | 0 | 0 | 0 |
| Queensland | Herbert | 1 | 2 | 1 | 0 | 0 |
| Queensland | Hinkler | 0 | 0 | 1 | 0 | 0 |
| Queensland | Kennedy | 1 | 3 | 0 | 0 | 0 |
| Queensland | Leichhardt | 4 | 4 | 2 | 0 | 0 |
| Queensland | Lilley | 0 | 0 | 1 | 0 | 0 |
| Queensland | McPherson | 0 | 1 | 0 | 0 | 0 |
| Queensland | Moncrieff | 74 | 231 | 2 | 0 | 0 |
| Queensland | Moreton | 1 | 1 | 1 | 0 | 0 |
| Queensland | Petrie | 1 | 1 | 0 | 0 | 0 |
| Queensland | Ryan | 1 | 2 | 0 | 0 | 0 |
| Queensland | Wide Bay | 4 | 2 | 0 | 0 | 0 |
| South Australia | Adelaide | 85 | 132 | 8 | 3 | 1 |
| South Australia | Barker | 0 | 0 | 1 | 0 | 0 |
| South Australia | Bass | 2 | 0 | 0 | 0 | 0 |
| South Australia | Boothby | 0 | 1 | 0 | 0 | 0 |
| South Australia | Denison | 13 | 1 | 0 | 0 | 0 |
| South Australia | Mayo | 28 | 169 | 3 | 0 | 0 |
| South Australia | Wakefield | 0 | 1 | 0 | 0 | 0 |
| Tasmania | Bass | 2 | 1 | 0 | 0 | 0 |
| Tasmania | Denison | 13 | 9 | 8 | 0 | 0 |
| Victoria | Ballarat | 2 | 2 | 1 | 0 | 0 |
| Victoria | Barton | 20 | 27 | 23 | 1 | 2 |
| Victoria | Batman | 0 | 1 | 0 | 0 | 0 |
| Victoria | Bendigo | 0 | 0 | 1 | 0 | 0 |
| Victoria | Calwell | 3 | 5 | 1 | 1 | 0 |
| Victoria | Canning | 1 | 1 | 0 | 0 | 0 |
| Victoria | Corangamite | 2 | 1 | 0 | 0 | 0 |
| Victoria | Corio | 4 | 3 | 2 | 0 | 0 |
| Victoria | Dunkley | 1 | 0 | 0 | 0 | 0 |
| Victoria | Flinders | 4 | 31 | 0 | 0 | 0 |
| Victoria | Forrest | 1 | 0 | 0 | 0 | 0 |
| Victoria | Gellibrand | 1 | 2 | 0 | 0 | 0 |
| Victoria | Gorton | 1 | 2 | 0 | 0 | 0 |
| Victoria | Higgins | 2 | 1 | 0 | 0 | 0 |
| Victoria | Holt | 4 | 1 | 0 | 0 | 0 |
| Victoria | Indi | 1 | 2 | 1 | 0 | 0 |
| Victoria | Isaacs | 2 | 7 | 0 | 0 | 0 |
| Victoria | Jagajaga | 0 | 1 | 0 | 0 | 0 |
| Victoria | Kooyong | 0 | 0 | 1 | 0 | 0 |
| Victoria | La Trobe | 2 | 2 | 0 | 0 | 0 |
| Victoria | Lalor | 2 | 1 | 1 | 0 | 0 |
| Victoria | McEwen | 0 | 1 | 0 | 0 | 0 |
| Victoria | McMillan | 1 | 0 | 0 | 0 | 0 |
| Victoria | Melbourne | 244 | 302 | 65 | 8 | 13 |
| Victoria | Melbourne Ports | 2 | 4 | 1 | 0 | 0 |
| Victoria | Menzies | 3 | 4 | 1 | 0 | 0 |
| Victoria | Murray | 0 | 1 | 0 | 0 | 0 |
| Victoria | Scullin | 278 | 367 | 0 | 0 | 0 |
| Western Australia | Curtin | 88 | 393 | 22 | 3 | 6 |
| Western Australia | Forrest | 8 | 12 | 1 | 0 | 0 |
| Western Australia | Fremantle | 2 | 5 | 2 | 0 | 0 |
| Western Australia | Hasluck | 2 | 1 | 0 | 0 | 0 |
| Western Australia | Moore | 1 | 0 | 0 | 0 | 0 |
| Western Australia | Perth | 2 | 1 | 0 | 0 | 0 |
| Western Australia | Swan | 0 | 1 | 0 | 0 | 0 |
Some of the results surprised me as I thought that the seats leaned Liberal or Labor and the tweets mentioned the other party more. After the results are in, I’m going to have to revisit this to see if there is any correlation between tweet volume by party in an electorate and the results for that electorate.
If anyone could make this into a map, that would be extremely awesome. A copy of the Excel file used to build these totals can be found here. Warning: it is 13 meg. If you want to see all the raw tweets and the keywords they were found under, AusVotes.csv. Warning: this file is 14 meg.