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Computer Science > Social and Information Networks

arXiv:1812.07135 (cs)
[Submitted on 18 Dec 2018]

Title:Globalness Detection in Online Social Network

Authors:Yu-Cheng Lin, Chun-Ming Lai, S. Felix Wu, George A. Barnett
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Abstract: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).
Comments: 6 pages, to be appeared in IEEE International Conference on Semantic Computing (ICSC2019)
Subjects: Social and Information Networks (cs.SI); Machine Learning (cs.LG); Machine Learning (stat.ML)
Cite as: arXiv:1812.07135 [cs.SI]
  (or arXiv:1812.07135v1 [cs.SI] for this version)
  https://doi.org/10.48550/arXiv.1812.07135

Submission history

From: Chun-Ming Lai [view email]
[v1] Tue, 18 Dec 2018 02:06:46 UTC (5,325 KB)
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Yu-Cheng Lin
Chun-Ming Lai
Shyhtsun Felix Wu
George A. Barnett
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