The findings showed that social media users act autonomously on some privacy issues, but are interdependent when information is co-owned by multiple users.
"Collaborative privacy management will be an even more pressing issue as the web becomes increasingly social and as big data technology becomes more prevalent," said Heng Xu, associate professor at Pennsylvania State University in the US.
As soon as individuals share information with their online social networks, they no longer have sole control over the information, but must rely on others for privacy protection.
"This is a paradigm shift, in a lot of ways, because most people think of privacy as being individualistic, but privacy is no longer just about the individual, it's also a collaborative and coordinated process," said Haiyan Jia, a post doctoral scholar at the Penn State.
Individuals rely on several strategies to deal with privacy rights for group content, such as group discussions and sensitive photos.
People are recognising that some content, which includes articles that are shared in a group or a picture with multiple people tagged in it, is co-constructed. In other words, this private information can also be co-owned.
According to the researchers, despite the growing importance of shared data, current social media sites lack tools for collaborative privacy management.
"Next-generation social networking platforms should consider built-in mechanisms to support group effort in privacy management," Jia noted.
For the study, the team recruited 304 people with an average age of 36 from Amazon Mechanical Turk -- a crowdsourced online work site.
The participants were asked to take a survey that lasted about 20 minutes.
To make sure the first sample was representative across different populations, researchers also recruited a second group of 427 undergraduate students to take the same survey.
The results showed that the undergraduate participants appeared less likely to limit who can access their shared content, indicating a generational difference.
The findings were presented at the recently held ACM Conference on Human Factors in Computing Systems in California.