Reducing　the　singling　overhead　for　tracking　and　mobile　paging　devices　is　a　challenging　issue　in　the　study　of　location　management　of　cellular　networks.　Cellular　networks　have　become　massive　generators　of　data,　and　in　the　forthcoming　years,　this　data　is　expected　to　increase　drastically.　Big　data-based　intelligence　and　analytics　can　improve　network　operational　efficiency　and　user　service　quality.　This　work　proposes　to　exploit　massive　handover　and　paging　data　from　cellular　networks　to　minimize　singling　due　to　user　mobility.　In　this　paper,　we　offer　a　new　holistic　tracking　area　lists　(TAL)　management　methodology,　considering　group　user　mobility　behavior　and　paging　characteristics.　Firstly,　a　series　of　graphs　showing　the　evolution　of　user　mobility　and　traffic　is　built　from　handover　and　paging　statistics　in　the　network　management　system　(NMS).　Then,　the　TAL　allocation　problem　is　formulated　as　a　classical　graph　partitioning　problem,　which　is　then　solved　by　detecting　overlapping　communities　algorithm　based　on　game　theory.　Results　show　that　the　proposed　method　can　effectively　reduce　the　location　management　singling　overhead　and　improve　the　TAL　configuration　efficiency.