People adopt unique personas for different social networking sites such as Facbook or LinkedIn, researchers including one of Indian origin have found.
"Users tend to portray themselves differently in these different worlds," said Dongwon Lee, associate professor at Pennsylvania State University in the US.
Researchers theorided that these different personas stem from a desire to fit within the distinctive culture or etiquette of each site.
For instance, a photo of someone's colorful drink may be popular on Instagram, but the same image post to LinkedIn would be frowned upon.
"The users tend to portray themselves differently in these different worlds," Lee explained.
Researchers compiled information on over 100,000 social media users by utilising their 'about.Me', a site that acts as a social media directory.
Upon analysing the profile pictures and biography information provided by these users, the team found some surprising differences in how different demographics portray themselves.
For example, the research showed that women were less likely to wear corrective eyewear, like reading glasses, in their profile pictures and users under the age of 25 were less likely to be smiling in their profile picture.
"The use of about.Me was the big breakthrough, as it allowed us to go from pairs of social networks, which we had been studying recently, to all the major social network platforms today: Facebook, Twitter, LinkedIn, and Instagram," said Nisanth Sastry of Pennsylvania State University.
The researchers do not believe that users are explicitly modifying their profile, but rather subconsciously adapting the behaviour modelled to fit in.
"The data shows that subtly, despite our best efforts, we do still fit stereotypes of gender and age in the way we tailor our personas," Sastry said.
"In the social media era, without realising it, people are leaving their marks. If we can tap into these digital footprints, then we can learn a lot about their behaviour," Lee said.
(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)