Towards Privacy-Preserved Query Optimization on Microblog Data

Microblog platform, such as Twitter and Sina, has been one of the major ways of information diffusion in modern society. However, although microblog has been proven to contain lots of information, it is really hard for people to find useful information on it. Besides, some information in microblog such as user IDs is not allowed to publish due to privacy policies. Thus the queries on microblog data can be regarded as privacy-preserved queries. One of the challenged issues is the poor performance of answering privacypreserved queries over microblog data, which owes to the large and increasing volume and the complex social network structure of microblog data. In this paper, we propose a basic idea to optimize the privacy-preserved queries on microblog data. We use a query-specific approach to treat the queries, i.e., the microblog data is first preprocessed according to the specific requirements of different types of queries, which are then organized through some indexing structures. Our preliminary experiments on real microblog data show that this approach has reasonable performance.