In this paper, we address the problem of difficult queries by using a novel strategy of collaborative query construction where the search engine would actively engage users in an iterative process to continuously revise a query. This approach can be implemented in any search engine to provide search support for users via a "Help Me Search" button, which a user can click on as needed. We focus on studying a specific collaboration strategy where the search engine and the user work together to iteratively expand a query. We propose a possible implementation for this strategy in which the system generates candidate terms by utilizing the history of interactions of the user with the system. Evaluation using a simulated user study shows the great promise of the proposed approach. We also perform a case study with three real users which further illustrates the potential effectiveness of the approach.

We propose Shapley Value based centrality measures for signed social networks. We also demonstrate that they lead to improved precision for the troll detection task.