Discouraging Abusive Behavior in Privacy-Preserving Online Social Networking Applications
Abstract
In this position paper we present the challenge of detecting abuse in a modern Online Social Network (OSN) while balancing data utility and privacy, with the goal of limiting the amount of user sensitive information processed during data collection, extraction and analysis. While we are working with public domain data available in a contemporary OSN, our goal is to design a thorough method for future alternative OSN designs that both protect user's sensitive information and discourage abuse. In this summary, we present initial results for detecting abusive behavior on Twitter. We plan to further investigate the impact of reducing input metadata on the quality of the abuse detection. In addition, we will consider defeating Byzantine behavior by opponents in the system.
Origin : Publisher files allowed on an open archive
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