1. A computer-implemented method comprising: using one or more computer processors: receiving a plurality of transaction records, each of the transaction records including data about a particular transaction engaged in by a member of a social networking service and including a geographic location and a timestamp of the particular transaction; scoring each of the plurality of transaction records based upon how recent the transaction occurred; clustering the plurality of transaction records into a plurality of clusters, each cluster including transaction records which contain geographic locations that are within a predetermined geographical radius from each other; creating an aggregate score for each particular one of the plurality of clusters based upon a sum total of the scores calculated for each transaction record clustered into the particular cluster; and creating a probability distribution based upon the scores for the plurality of clusters, the probability distribution indicating a probability that the member was in each of the plurality of geographic locations represented by the plurality of clusters; determining, over a predetermined period of time, that a number of unique locations with a probability greater than a predetermined probability threshold in the probability distribution exceeds a predetermined location threshold; responsive to determining that the number of unique locations exceeds the location threshold, classifying the member as a traveler; responsive to determining that the member is a traveler, determining a scope of travel of the member, wherein the scope of travel is one of: regional, national, or international, the determining the scope of travel of the member determined based upon an average distance between the number of unique locations with the probability greater than the probability threshold in the probability distribution; and recommending, in a user interface, other members with a same scope of travel as the member to connect to the member or to follow companies with which they may be interested in following.