The workforce analyzer: group discovery among LinkedIn public profiles

In this paper, we describe two users’ group discovery methods among LinkedIn public profiles. We start by clustering profiles according to their professional background. In this sense, we combine the so-called K-means technique with the gap statistics method and use tag clouds to scrutinize the obtained groups. The second phase of this work consists in classifying the same profiles by relying on a knowledge base. In this context, we design a support-vector-machines multi-label classifier that takes advantage of the LinkedIn job Ads taxonomy. We finally contrast results of both methods and provide insights about the trending professional orientations of the workforce from an online perspective.

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