human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "network structure and resilience of mafia syndicates"
  Abstract: In this paper we present the results of our study of Sicilian Mafia organizations using social network analysis. The study investigates the network structure of a Mafia syndicate, describing its evolution and highlighting its plasticity to membership-targeting interventions and its resilience to disruption caused by police operations. We analyze two different datasets dealing with Mafia gangs that were built by examining different digital trails and judicial documents that span a period of ten years. The first dataset includes the phone contacts among suspected individuals, and the second captures the relationships among individuals actively involved in various criminal offenses. Our report illustrates the limits of traditional investigative methods like wiretapping. Criminals high up in the organization hierarchy do not occupy the most central positions in the criminal network, and oftentimes do not appear in the reconstructed criminal network at all. However, we also suggest possible strategies of intervention. We show that, although criminal networks (i.e., the network encoding mobsters and crime relationships) are extremely resilient to different kinds of attacks, contact networks (i.e., the network reporting suspects and reciprocated phone calls) are much more vulnerable, and their analysis can yield extremely valuable insights.

Connected through hyperedge HE-1 (induced by source paper "disrupting resilient criminal networks through data analysis the case of sicilian mafia"):
  with members:
    - "visualizing criminal networks reconstructed from mobile phone records"

Connected through hyperedge HE-2 (induced by source paper "a complex networks approach to find latent clusters of terrorist groups"):
  with members:
    - "generalized network dismantling"

Connected through hyperedge HE-3 (induced by source paper "contagion dynamics of extremist propaganda in social networks"):
  with members:
    - "the rise of jihadist propaganda on social networks"
    - "disinformation and social bot operations in the run up to the 2017 french presidential election"
    - "online human bot interactions detection estimation and characterization"
    - "predicting online extremism content adopters and interaction reciprocity"
    - "the darpa twitter bot challenge"
    - "spider and the flies focused crawling on tumblr to detect hate promoting communities"
    - "the rise of social bots"
    - "bots strongerin and brexit computational propaganda during the uk eu referendum"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SI(Social and Information Networks)