Twitter misrepresents the real world, computer scientists warn
Latest figures on Twitter suggest that just five per cent of over 65s use the platform compared with 35 per cent for those aged 18-29. Similarly far more men use the social networking site than women.
Instagram has a particular appeal to younger adults, urban dwellers, and non-whites.
In contrast, the picture-posting site Pinterest is dominated by females aged between 25 and 34. LinkedIn is especially popular among graduates and internet users in higher income households.
Although Facebook is popular across a diverse mix of demographic groups scientists warn that postings can be skewed because there is no dislike button. There are also more women using Facebook than men, 76 per cent of female internet users use the site compared with 66 per cent of males.
A common assumption underlying many large-scale social media-based studies of human behaviour is that a large-enough sample of users will drown our noise introduced by peculiarities of the platforms population, said lead author Derek Ruths, an assistant professor in McGill's School of Computer Science.
These sampling biases are rarely corrected for, if even acknowledged.
The researchers also claim that the way in which sites direct people to links also leads to interest bias. The design of a platforms can dictate how users behave and, therefore, limit what behaviour can be measured.
And a large number of spammers and bots, which masquerade as normal users on social media, get mistakenly incorporated into measurements and predictions of human behaviour.
In recent years, studies have claimed the ability to predict everything from summer blockbusters to fluctuations in the stock market through social media. Some researchers say it is possible to map the spread of disease.
But the computer scientists claim the flaws in big data sets for research could have huge implications. Thousands of research papers each year are based on skewed information taken from social media, they claim.
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Twitter misrepresents the real world, computer scientists warn