On sampling the wisdom of crowds: random vs. expert sampling of the twitter stream

Several applications today rely upon content streams crowd-sourced from online social networks. Since real-time processing of large amounts of data generated on these sites is difficult, analytics companies and researchers are increasingly resorting to sampling. In this paper, we investigate the crucial question of how to sample the data generated by users in social networks . The traditional method is to randomly sample all the data. We analyze a different sampling methodology, where content is gathered only from a relatively small subset (