It is harder to maintain anonymity due to the use of social networking sites, claim researchers.
They were able to identify many people in supposedly anonymous data sets by analysing links between users of social sites. Social sites sell anonymised data to marketing firms to generate cash.
The researchers now suggest that web firms should do more to protect users' privacy.
The data sets are usually stripped of personally identifiable information, such as names, before it is sold to marketing companies or researchers keen to plumb it for useful information.
Before now, it was thought sufficient to remove this data to make sure that the true identities of subjects could not be reconstructed. But an algorithm has been developed which allows the anonymous data to be reverted to names and addresses.
Computer scientists Arvind Narayanan and Dr Vitaly Shmatikov, from the University of Texas at Austin, developed the algorithm. It looks at relationships between all the members of a social network - not just the immediate friends that members of these sites connect to.
Social graphs from Twitter, Flickr and Live Journal were used in the research.
They found that one third of those on both Flickr and Twitter can be identified from the completely anonymous Twitter graph, despite the fact that the overlap of members between the two services is thought to be just 15%.
The results also had implications for the social sites themselves, wrote the researchers.
"Social-network operators should stop relying on anonymisation as the 'get out of jail' card, insofar as user privacy is concerned," they said.
"They should inform users when their information is disclosed to third parties, even if this information has been anonymised, and give them the opportunity to opt out," they added.
Writing about their work, the two researchers said many different organisations might be interested in reconstructing the true identities.
As social network sites become more heavily used people will find it increasingly difficult to maintain a veil of anonymity.
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