Maintaining a Consistent Representation of Self across Multiple Social Networking Sites -- A Data-centric Perspective

The rising pervasiveness and use of sensitive data on Social Networking Sites (SNS) requires careful consideration of one's privacy while using such sites. Also, users faced with a multitude of online contacts from various areas of life feel the need to create multiple representations of self and keeping them consistent. The difficulty of this task is compounded by the use of multiple SNS. We argue that for maintaining a consistent representation of self across multiple SNS, it needs to be carefully analyzed how personal attributes, which make up the online identity, are implemented and stored on each site. In this paper, we analyze criteria to classify how attributes and their values are implemented at SNS. Then, we present a structured approach to transform attribute values for use on multiple SNS. We evaluate the approach by applying it to selected attributes of major SNS.

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