The results, especially the high numbers stated in the news article (68% recall, 90% accuracy) are overestimated as their verification method (i.e., whether the LLM detected really the right account) come from matching veryfied accounts with a test set of anonymous accounts of which they knew the real name. They knew the real name bcs the persons had a public link to their LinkedIn in their “anonymous” profile (which was removed for the sake of testing wheter the LLm can match the two acfounts. That being said: a user who uses a pseudonym but links his/her account publically to a, say, LinkedIn account doesn’t really care about anonymity and might hand out many more ‘breadcrumbs’ to follow than a truly anonymous account.
But I still think that also in the case of a fully anonymous account, people can be fingerprinted and matched with non-anonymous identities due to language, style etc. by a LLM.
The results, especially the high numbers stated in the news article (68% recall, 90% accuracy) are overestimated as their verification method (i.e., whether the LLM detected really the right account) come from matching veryfied accounts with a test set of anonymous accounts of which they knew the real name. They knew the real name bcs the persons had a public link to their LinkedIn in their “anonymous” profile (which was removed for the sake of testing wheter the LLm can match the two acfounts. That being said: a user who uses a pseudonym but links his/her account publically to a, say, LinkedIn account doesn’t really care about anonymity and might hand out many more ‘breadcrumbs’ to follow than a truly anonymous account.
But I still think that also in the case of a fully anonymous account, people can be fingerprinted and matched with non-anonymous identities due to language, style etc. by a LLM.