Australian attitudes on climate action

All six pages of the dashboard are interactive, and you can apply filters.

Tweets and comments were analysed through:

Sentiment and Emotion Analysis

Distribution of sentiment polarity on a histogram (top left): shows the distribution of positive and negative sentiment values. The sentiment polarity is recorded on a scale of -1 to +1. Negative sentiment is from -1 to 0, and positive is from 0 to 1. Hover over the figures for further details.

Bar chart: illustrates the strength of the emotions (Trust, Joy, Fear, Surprise, Anger, Disgust, Anticipation, Sadness). The higher the bar, the stronger the emotion.

Age Analysis

The deep learning method, based on description users provided in their profile, predicts age ranges (under 30, 30-45, 45-60, and 60+). If the user does not have a description, or, an account associated with an institution, the Age is assigned as ‘unknown’.

Topics Discussed

The deep learning method trained after human expert annotations predicts topics discussed in the twitter post. The following topics were considered: 'Agriculture', 'Bushfire', 'Carbon Farming', 'Carbon price Offsets', 'Clean Renewable Energy', 'Climate Change Denial', 'Climate Change Scepticism', 'Climate Policy', 'Climate Resilience', 'Coastal Erosion', 'Coral Bleaching', 'Drought', 'Ecosystem Collapse', 'Financial Disclosure', 'Flooding', 'Fossil Fuel', 'Hydrogen', 'Indirect Direct Emissions', 'Insurance Coverage', 'Jobs', 'Managed Retreat', 'Mass Wildlife Kills', 'Nature Based Solutions', 'Net Zero Target', 'Others', 'Party Politics', 'Sea Level Rise', 'Species Migration', 'Transportation', 'Water Security'.