Online and offline data is now gradually integrated, and help marketers advertising more accurately, which has become a trouble for those digital privacy supporters. They will firstly assess users’ consumer capacity, evaluate their budget and price sensitivity, and then push advertisement according to private data.

That’s how we fall into the trap of marketers. Some people might say, it’s a win-win situation, consumers can get what they need by being screened. However, are these things really what we need, or is it a rational price? During this process, consumers have fewer options. We pay more promotion fee rather than the product itself.

Associative effect

Many people cannot imagine that combining a series of information from you, your college, your neighbours can cause doubtful effects. For a social website such as Facebook, it is easy to set up a social graph to connect users. The friend circle mode suggests that significant personal data can be determined by analyzing his network of friends.

Cater Jernigan and Behram F.T Mistree’s did a test in MIT Facebook network, ‘We tested the hypothesis that the sexual orientation of a given Facebook user can be determined based on the sexual orientations of that user’s friends and found that self-reporting gay male MIT Facebook users have almost an order of magnitude higher percentage of gay male friends than heterosexual male users.’[14]

Figure 1: Social graph revealing Facebook friendship associations between self–identified gay male students in the MIT network.

Another example shows the power of data combination. As Daniel J. Solove says in his book[15], ‘Suppose you bought a book about cancer. This purchase isn’t very revealing on its own, for it just indicates an interest in the disease. Suppose you bought a wig. The purchase of a wig, by itself, could be for a number of reasons. But combine these two pieces of information, and now the inference can be made that you have cancer and are undergoing chemotherapy.’ In this way, it does not depend on you whether to post this information or not.


Researchers Adam Sadilek from the Rochester College and labs engineer John Krumm from Microsoft found that they can roughly predict a person’s future position. ‘We propose an efficient nonparametric method that extracts significant and robust patterns in location data, learns their associations with contextual features (such as day of the week) and subsequently leverages this information to predict the most likely location at any given time in the future.’ [16] As the name for their system – “Far Out” says, that’s where the personal information will take us to in the big data era.

Harass, even crime

You must feel no stranger to calls harassment and litter messages. One time you search something on the search engines, you may receive a phone call about this someday. Disclosure of privacy can even lead to crime. For example, criminals could use leaked information to forge the identity and carry out various criminal activities, which can cause considerable trouble for who are taken advantage of. They can even use the information such as family members and addresses, etc, to defraud and abduct.