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Extracting Social Relationships from Social Software
Abstract
We present an analytical approach to detect relationships between persons in the real world, such as friendship, rivalry, or others, out of the behavior of members in a social software system. In social software systems, users often evaluate submissions of other users. If these actions are somehow biased, we assume a personal relationship between these users. If we know about the relationship between two users, the validity of the evaluation, and with that, the trust into the social software, can be improved. For example, if a rival evaluates a submission unfairly, we should decrease the impact of this evaluation. We apply the approach in TechScreen, a social software system that supports the exchange of knowledge about Internet technologies. Since we try to mine competencies of its users, the validity of evaluations is very important. In this chapter we show results of experiments with about 50 users.
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