?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.relation=http%3A%2F%2Feprints.imtlucca.it%2F2394%2F&rft.title=Tail-scope%3A+using+friends+to+estimate+heavy+tails+of+degree+distributions+in+large-scale+complex+networks&rft.creator=Eom%2C+Young-Ho&rft.creator=Jo%2C+Hang-Hyun&rft.subject=HA+Statistics&rft.subject=QC+Physics&rft.description=Many+complex+networks+in+natural+and+social+phenomena+have+often+been+characterized+by+heavy-tailed+degree+distributions.+However%2C+due+to+rapidly+growing+size+of+network+data+and+concerns+on+privacy+issues+about+using+these+data%2C+it+becomes+more+difficult+to+analyze+complete+data+sets.+Thus%2C+it+is+crucial+to+devise+effective+and+efficient+estimation+methods+for+heavy+tails+of+degree+distributions+in+large-scale+networks+only+using+local+information+of+a+small+fraction+of+sampled+nodes.+Here+we+propose+a+tail-scope+method+based+on+local+observational+bias+of+the+friendship+paradox.+We+show+that+the+tail-scope+method+outperforms+the+uniform+node+sampling+for+estimating+heavy+tails+of+degree+distributions%2C+while+the+opposite+tendency+is+observed+in+the+range+of+small+degrees.+In+order+to+take+advantages+of+both+sampling+methods%2C+we+devise+the+hybrid+method+that+successfully+recovers+the+whole+range+of+degree+distributions.+Our+tail-scope+method+shows+how+structural+heterogeneities+of+large-scale+complex+networks+can+be+used+to+effectively+reveal+the+network+structure+only+with+limited+local+information&rft.publisher=ArXiv&rft.date=2014-11&rft.type=Working+Paper&rft.type=NonPeerReviewed&rft.identifier=++Eom%2C+Young-Ho+and+Jo%2C+Hang-Hyun++Tail-scope%3A+using+friends+to+estimate+heavy+tails+of+degree+distributions+in+large-scale+complex+networks.++Working+Paper++%23+%2F2014++++ArXiv+++++++(Unpublished)+++&rft.relation=http%3A%2F%2Farxiv.org%2Fabs%2F1411.6871