Λεπτομέρειες

ΕίδοςΔημοσίευση
ΚωδικόςTR-2014-8
ΤίτλοςRegionally Influential Users in Location-Aware Social Networks
ΣυγγραφέαςBouros P., Sacharidis D., Bikakis N.
Έτος2014
Λέξεις κλειδιάlocation-aware services, social networks, propagation model, influence maximization, graph closeness centrality, LASN, location-based social networks, LBSN, ranking, top-k
ΠερίληψηThe ubiquity of mobile location aware devices and the proliferation of social networks have given rise to Location-Aware Social Networks (LASN), where users form social connections and make geo-referenced posts. The goal of this paper is to identify users that can influence a large number of important other users, within a given spatial region. Returning a ranked list of regionally influential LASN users is useful in viral marketing and in other per-region analytical scenarios. We show that under a general influence propagation model, the problem is #P-hard, while it becomes solvable in polynomial time in a more restricted model. Under the more restrictive model, we then show that the problem can be translated to computing a variant of the so-called closeness centrality of users in the social network, and devise an evaluation method.
ΚατηγορίαSpatiotemporal Databases
Δημοσίευση22nd ACM International Conference on Advances in Geographic Information Systems (ACM GIS SIGSPATIAL'14)
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