Think you can tell a man from a woman, a PhD from someone who never attended college, a conservative from a liberal, based solely on the content of their social media feeds? Yeah, well so did social psychologists and computer scientists from the University of Pennsylvania Positive Psychology Center, Germany, and Australia and they were all dead wrong.

A series of studies were conducted by the researchers in which test subjects were asked to categorize the authors of tweets based solely on the content of their social media posts. They assigned the posts to categories of writer's gender, age, political orientation, oreducation level.

The scientists used natural language processing (NLP) algorithms – a form of artificial intelligence – to parse through the stereotyping of which we are all guilty when we try to judge someone solely upon their social media expression.

"These inaccurate stereotypes tended to be exaggerated rather than backwards," says lead author Jordan Carpenter. "For instance, people had a decent idea that people who didn't go to college are more likely to swear than people with PhDs, but they thought PhDs never swear, which is untrue."

You would think that in the midst of the recent election's social media firestorm people's judgement regarding political affiliations would be more finely tuned, but no:

"One of our most interesting findings is the fact that, when people had a hard time determining someone's political orientation, they seemed to revert (unhelpfully) to gender stereotypes, assuming feminine-sounding people were liberal and masculine-sounding people were conservative," said Carpenter.

For example, people assumed that men were more likely to post about technology – and they're right. But this stereotype led to immediate false conclusions about nearly every woman who posted about technology.

"One important aspect of this research is that it reverses the way a lot of stereotype research has been done in the past," said Daniel Preotiuc-Pietro, a co-author of the study.

Rather than starting with various groups and asking people what behaviors they associate with them, the scientists started with a set of behaviors and asked people to state the group identity of the person who did them. They also "considered stereotypes as a lexical 'web': the words we associate with a group are themselves our stereotype of that group," writes Preotiuc-Pietro.

"This is a novel way around the problem that people often resist openly stating their stereotypes, either because they want to present themselves as unbiased or because they're not consciously aware of all the stereotypes they use," says Carpenter.

The research was published in Social Psychological and Personality Science.