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DTSTART;TZID=Europe/Amsterdam:20210731T090000
DTEND;TZID=Europe/Amsterdam:20210731T091500
DTSTAMP:20260506T163821
CREATED:20210719T063152Z
LAST-MODIFIED:20211029T100325Z
UID:556-1627722000-1627722900@www.popnet.io
SUMMARY:The emergence of hierarchy in spatial diffusion over the life-cycle of innovations
DESCRIPTION:Conference talk at IC2S2 \n\n\n\nAuthors: Eszter Bokanyi\, Martin Novák\, Ákos Jakobi and Balazs Lengyel \n\n\n\nABSTRACTUsing a model capturing distance-decay\, urban scaling\, and hierarchical difference\, we show that hierarchical diffusion has an increasing role over the life cycle in the spatial adoption of an online social network.
URL:https://www.popnet.io/events/the-emergence-of-hierarchy-in-spatial-diffusion-over-the-life-cycle-of-innovations/
CATEGORIES:Conference talk
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DTSTART;TZID=Europe/Amsterdam:20210731T170000
DTEND;TZID=Europe/Amsterdam:20210731T183000
DTSTAMP:20260506T163821
CREATED:20210719T074614Z
LAST-MODIFIED:20211029T100317Z
UID:568-1627750800-1627756200@www.popnet.io
SUMMARY:Measuring Anonymity in Complex Networks
DESCRIPTION:Poster presentation by Rachel de Jong at IC2S2 conference \n\n\n\nAuthors: Rachel de Jong; Mark van der Loo; Frank Takes \n\n\n\nComplex networks are often used to describe the interactions between individuals or organizations within social or economic systems. In order to comply with regulations regarding privacy and data protection\, such data is frequently anonymized by leaving out personal identifiers of the nodes. However\, in such cases (properties of) a seemingly anonymized individual may still be re-identified based on its structural position in the network [1]. \n\n\n\nThis is particularly relevant for National Statistical Institutes (NSIs) that are applying network science to population scale social network data [2]. When releasing data for research purposes\, NSIs rely on statistical disclosure control (SDC) techniques for data protection [3]. A central concept in this field is anonymity: the number of equivalent data points in an anonymized data set. Anonymity is an essential component in assessing the risk of disclosure. \n\n\n\nThis work presents a method for measuring the disclosure probability of nodes in networks\, that takes as a parameter the amount of information an adversary has about a node’s surrounding structure. We also provide an in-depth analysis of node anonymity in three well-known complex network models. The proposed j-anonymity distributions can be used to measure disclosure probabilities\, which in turn can be used to assess disclosure risk. Numerical experiments reveal that many nodes are de-anonymized when their neighbourhood of radius 2 is known.
URL:https://www.popnet.io/events/measuring-anonymity-in-complex-networks/
CATEGORIES:Conference talk
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