The concept of the enterprise social graph (Forbes, 2010) has been garnering more and more attention over the last several years from increasingly large companies. The idea is simple: Exploit an enterprise's internal social media network to provide an agile management and analysis tool for HR. However, not all companies can rely on specific in-house social platforms to gather and/or analyze data, nor do they always have the competencies or time to handle such huge volumes of data. In this presentation, we will share innovative methods to visualize, navigate and manage a company's employee network to facilitate the management of key HR practices — which is rooted in Neo4j, Cypher and Python. We will demonstrate the effectiveness of this approach through the use of real company data.
Claudio Borile is a Data Scientist at aizoOn s.r.l., a technology consulting group active in Europe, U.S. and Australia, working on complex networks analysis and data driven modeling in Big Data. In 2016 he was awarded of a Lagrange project research grant from the I.S.I. foundation in Turin, Italy, for an applied research on Big Data and Network analysis on social media, where he consolidated his skills in data science and Big Data tools such as Neo4j and Spark. He got his Ph.D in Theoretical Physics from the University of Padova, Italy in 2013 with a thesis on agent-based models on graphs, and after that he worked as a postdoc for the Hugef Foundation in Torino, Italy for two years, working on mathematical models and message-passing algorithms for deep learning.