Predicting which way you'll vote tomorrow could come down to a simple "like" on Facebook.
That's according to a University of Canterbury PhD researcher who has published a new paper looking at how publicly available social media activity can tell us much about voter intentions.
"We leave digital traces behind whenever we click on something on the web," Jakob Baek Kristensen said.
"This research shows that a person's political 'likes' on Facebook can predict the party they vote for with fairly high accuracy."
Marketing firms such as Cambridge Analytica, which claim to have secured the victory of Donald Trump and the Brexit campaign, were attributing their abilities to the predictive powers of big and broad data.
Although the area was still largely unexplored, Kristensen's research showed that only very little, publicly available data was needed to predict which way someone would vote.
By liking politicians' public Facebook posts, a person's voting intention could be predicted with up to 70 per cent accuracy in a multi-party system.
"A few selective digital traces produce prediction accuracies that are on par or even greater than most current approaches based upon bigger and broader datasets.
"Combining the online and offline, we connect a subsample of surveyed respondents to their public Facebook activity and apply machine learning classifiers to explore the link between their political liking behaviour and actual voting intention.
"Through this work, we show that even a single selective Facebook 'like' can reveal as much about political voter intention as hundreds of heterogeneous 'likes'.
Within the field of election forecasting, research has shown the potential for predicting election outcomes based on digital data from a diverse range of platforms including YouTube, Google, Twitter, Facebook, and even Wikipedia.
"The techniques we developed are not language dependent and can be employed in any country where Facebook is popular with the general population," he said.
"Future work will involve drawing on the results from our paper and using them to make election result predictions."