Portela García-Miguel, JavierGarcía Villalba, Luis JavierSilva Trujillo, Alejandra GuadalupeSandoval Orozco, Ana LucilaKim, Tai-Hoon2023-06-182023-06-182016-11-011424-822010.3390/s16111832https://hdl.handle.net/20.500.14352/19229Social network analysis aims to obtain relational data from social systems to identify leaders, roles, and communities in order to model profiles or predict a specific behavior in users’ network. Preserving anonymity in social networks is a subject of major concern. Anonymity can be compromised by disclosing senders’ or receivers’ identity, message content, or sender-receiver relationships. Under strongly incomplete information, a statistical disclosure attack is used to estimate the network and node characteristics such as centrality and clustering measures, degree distribution, and small-world-ness. A database of email networks in 29 university faculties is used to study the method. A research on the small-world-ness and Power law characteristics of these email networks is also developed, helping to understand the behavior of small email networks.engAtribución 3.0 Españahttps://creativecommons.org/licenses/by/3.0/es/journal articlehttps://doi.org/10.3390/s16111832https://www.mdpi.com/1424-8220/16/11/1832open accessanonymityemail networkgraph theoryprivacysocial network analysissmall-world-nessstatistical disclosure attackRedesEstadística1209 Estadística