The Digital Observatory @ QUT @digitalobservatory.bsky.social · 04/05/2025Let's return to our political discussion on Reddit data (roughly same volume as our NewsTalk dataset). Now let's consider support and oppose separately, and put LNP, ALP, Greens and All in the same plot. I include 'All' primarily to capture negative sentiment to all parties on key issues. 010 1
The Digital Observatory @ QUT @digitalobservatory.bsky.social · 04/05/2025I've applied our AI pipeline to process Australia news website comments (The Digital Observatory's NewsTalk product). I've broken it down by the top 8 news websites (for reader comments) with subplots for the ALP vs LNP. 110 1
The Digital Observatory @ QUT @digitalobservatory.bsky.social · 18/04/2025Week 3 report might be a bit late since most of us are on leave next week, but here's top topic Reddit political party sentiment visualisation for week three of the election campaign anyway. Negative sentiment towards LNP re nuclear and renewables is well up this week. Greens support up re housing. 000 0
The Digital Observatory @ QUT @digitalobservatory.bsky.social · 11/04/2025AI analysis of many thousands of comments by Australians on federal election topics, indicating political support/opposition by major parties. For more, see www.digitalobservatory.net.au/blog/what-do... 000 0
The Digital Observatory @ QUT @digitalobservatory.bsky.social · 06/03/2025But by and large, there is a striking reduction in the complexity of language. I was motivated to look into this after seeing the the difference between Trump's earlier and contemporary speech in the source dataset. To show it in absolute terms: 010 1
The Digital Observatory @ QUT @digitalobservatory.bsky.social · 06/03/2025This is lexical diversity plots of 40+ years of Donald Trump speech (~38 million words), organised by parts-of-speech. See bumps to adjective diversity when he took to inventing silly names for opponents. Data ripped from Factbase rollcall.com/factbase/. 121 2