Information Flow and Search in Unstructured Keyword Based Social Networks

In online social networks (OSNs), user connections can be represented as a network. The network formed has distinct properties that distinguish it from other network topologies. In this work, we consider an unstructured keyword based social network topology where each edge has a trust value associated with it to represent the mutual relationship between the corresponding nodes. Users have keywords as their profile attributes that have policies associated with them to define abstractly the flow of keyword information and the accessibility to other users in the network. We also address privacy concerns as outlined in works on future OSN architectures. This paper makes two key contributions. First, we develop an information flow model to disseminate keyword information when users add keywords as their profile attributes. Second, for keyword based queries, we design and develop a search algorithm to find users with the specified keywords in their profile attributes. It is based on a linear combination of topological distance and trust metrics. It is also dynamic in nature such that it adapts itself for each individual node during the search process. We observe an improvement in orders of magnitude when the search algorithm is compared to breadth first search.