1. A method for extracting customer feedback from a first microblog site, the method comprising: capturing microblog updates posted by customers from said first microblog site; filtering the captured microblog updates according to filter criteria that remove non-actionable items from the captured microblog updates; prioritizing the filtered microblog updates, wherein said prioritizing comprises assigning probabilities to corresponding filtered microblog updates, said assigning based on influence scores of the customers determined using one or more scoring services different from the first microblog site, popularity of each of the customers based on number of followers of said customer on said first microblog site, results from monitoring one or more microblog sites different from said first microblog site for one or more postings made by the customers, and proximities of the customers to businesses associated with the filtered microblog updates, said proximities determined by analyzing metadata, hashtags associated with said filtered microblog updates, and check-in information obtained from one or more sites different from said microblog site, further wherein each said probability is used to indicate confidence that the corresponding filtered microblog update is actionable, and assigning priorities to said corresponding filtered microblog updates based on said assigned probabilities; tagging the filtered microblog updates based on the corresponding assigned priorities, and discarding at least one of the filtered microblog updates based on said tagging, wherein said discarding is based on an intelligent dropping policy and congestion levels; and classifying the prioritized microblog updates, said classifying comprising selecting at least some of the prioritized microblog updates based on said tagging, and determining whether each selected microblog update is actionable.