  Classification problems have made significant progress due to the maturity of
artificial intelligence (AI). However, differentiating items from categories
without noticeable boundaries is still a huge challenge for machines -- which
is also crucial for machines to be intelligent.
  In order to study the fuzzy concept on classification, we define and propose
a globalness detection with the four-stage operational flow. We then
demonstrate our framework on Facebook public pages inter-like graph with their
geo-location. Our prediction algorithm achieves high precision (89%) and recall
(88%) of local pages. We evaluate the results on both states and countries
level, finding that the global node ratios are relatively high in those states
(NY, CA) having large and international cities. Several global nodes examples
have also been shown and studied in this paper.
  It is our hope that our results unveil the perfect value from every
classification problem and provide a better understanding of global and local
nodes in Online Social Networks (OSNs).
