You can tweet but you can’t hide

RT reports that researchers have shown that we unconsciously reveal much more information about ourselves than we realise; both through what and how we write, and through the technology we use. Quote.

Twitter?s metadata contains an array of revealing information on its users, a new study proves, and can be used to identify a user with unnerving accuracy ? even those who go to great lengths to hide that information.

Researchers at University College London and the Alan Turing Institute found they could correctly identify a Twitter user from a group of 10,000 with 96.7 percent accuracy, using just their tweets and publicly available metadata.

The goal was ?to determine if the information contained in users? metadata is sufficient to fingerprint an account,? and the results reveal how much identifying information is tied to Twitter accounts, whose users may believe they are tweeting anonymously. A single tweet contains about 144 fields of metadata.

?That?s the mentality with metadata,? the study?s lead co-author Beatrice Perez of University College London told Wired. ?People think it?s not a big deal.?

Researchers took 14 pieces of metadata from 5 million Twitter accounts ? including the date the account was created, its followers, the accounts it follows and the tweets it likes ? and ran it through three machine-learning algorithms. The researchers found the most basic algorithm had the most accuracy.

The methods of identifying users could be used if an account changes its name, if a user has created multiple accounts or to tell if legitimate accounts have been taken over by malicious users.

The researchers also found obfuscation strategies are ineffective, as even when 60 percent of the data was muddled or altered, the user was able to be classified with an accuracy of more than 95 percent.

When the researchers widened their scope and searched for the 10 most likely candidates, their accuracy was 99.22 percent.

While the study uses Twitter as its subject, its authors note ?the methods presented in this work are generic and can be applied to a variety of social media platforms with similar characteristics in terms of metadata.?

The researchers say the results have strong implications in terms of ?the design of metadata obfuscation strategies? not just for Twitter, but for most social media platforms. End of quote.

The introduction to the research paper says: Quote.

[Researchers have shown] that the content of a message posted on an online social network platform reveals a wealth of information about its author. Through text analysis, it is possible to derive age, gender, and political orientation of individuals (Rao et al. 2010); the general mood of groups (Bollen, Mao, and Pepe 2011) and the mood of individuals (Tang et al. 2012). Image analysis reveals, for example, the place a photo was taken (Hays and Efros 2008), the place of residence of the photographer (Jahanbakhsh, King, and Shoja 2012), or even the relationship status of two individuals (Shoshitaishvili, Kruegel, and Vigna 2015). If we look at mobility data from location-based social networks, the check-in behavior of users can tell us their cultural background (Silva et al. 2014) or identify users uniquely in a crowd (Rossi and Musolesi 2014).End of quote.

My question would be, if it is that easy for researchers to identify a user, why can’t Twitter, Facebook, et al with all their computing power and programmers find and kill off all the bots that derailed Hilary and allowed Trump to win? After all, it was the Russians what did it, not the voters.