Anonymized location data won't necessarily preserve your anonymity.

M. Keith Chen, associate professor of economics at UCLA's Anderson School of Management, and Ryne Rohla, a doctoral student at Washington State University, accomplished this minor miracle of data science by assuming that the GPS coordinates transmitted by mobile phones between 1am and 4am over several weeks represent the location of device owners' homes.

"If a person has a consistent early morning location over the three weeks before Thanksgiving, we use this location as a simple proxy for their 'home,'" they explain in a draft research paper.

It's far from foolproof, but good enough for government, or in this case academic, work.

Chen and Rohla used this information to determine that political advertising related to the divisive 2016 election had caused enough tension in families that people cut short their Thanksgiving visits last year with relatives holding opposing political views.

Party affiliation in this case was calculated as a ratio based on voting precinct results (eg. 52 per cent Democrat, 48 per cent Republican) rather than as an attempt to determine household party affiliation. So that aspect of personal privacy remains intact.

But it's the supposedly anonymous location data that proves to be problematic. The researchers obtained it from Safegraph, a company that aggregates location data from multiple mobile apps, but it could have come from other data traders.

Safegraph tracks the location of 10 million Americans' phones, according to the researchers, who used the company's dataset of 17 billion location pings collected in November 2016 to infer the residences of 5 million individuals.

The Register asked Safegraph for comment but has not yet received a response. On its website, the company downplays the value of such information by referring to it as "mobile location exhaust data," as if it were an unwanted waste product.

Now it may be that the apps sharing location info with Safegraph obtained this information through the usual means – a click-agreement designed to elicit user consent from individuals who didn't read the terms of the deal. And if they did give the matter some thought, they probably assumed they were just signing away coordinates that couldn't be traced back to them.

Anonymized location data, particularly when combined with other data, can be quite revealing. Beyond the obvious inference that a mobile phone's repeated resting place in the middle of the night is probably home base, de-anonymization has been demonstrated with credit card transaction data, Netflix customer records, and patient health records.

In 2013, researchers at MIT and Belgium's Université Catholique de Louvain found that four points of reference were enough to identify 95 per cent of individuals in a data set of anonymized mobile phone data.

It's time to stop using the term "anonymized" in the context of location information. Try "temporarily hidden." ®