Computer scientists have built a new tool that may enable them to detect fake profiles on an adult content website — believed to be heavily targeted by “catfishes” to befriend other users and gain more profile views.
The study found that 40 per cent of the users lied about their age and nearly a quarter lied about their gender.
Interestingly, women were more likely to deceive than men.
“Adult websites are populated by users who claim to be other than who they are, so these form perfect testing grounds for techniques that identify catfishes,” said Walid Magdy from the University of Edinburgh.
“We hope that our development will lead to useful tools to flag dishonest users and keep social networks of all kinds safe,” Magdy added.
The study will be presented at the International Conference on Advances in Social Networks Analysis and Mining in Australia.
The researchers built their model on data retrieved from 5,000 verified profiles on the website.
These profiles were used to train the model to estimate the gender and age of a user with high accuracy, using their style of writing in comments and network activity.
This enabled the models to accurately estimate age and gender of users with unverified accounts, and spot misinformation from fake accounts, the researchers said.