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: "locating contagion sources in networks with partial timestamps"
  Abstract: This paper studies the problem of identifying the contagion source when partial timestamps of a contagion process are available. We formulate the source localization problem as a ranking problem on graphs, where infected nodes are ranked according to their likelihood of being the source. Two ranking algorithms, cost-based ranking (CR) and tree-based ranking (TR), are proposed in this paper. Experimental evaluations with synthetic and real-world data show that our algorithms significantly improve the ranking accuracy compared with four existing algorithms.

Connected through hyperedge HE-1 (induced by source paper "dandelion redesigning the bitcoin network for anonymity"):
  with members:
    - "hijacking bitcoin routing attacks on cryptocurrencies"
    - "hijacking bitcoin large scale network attacks on cryptocurrencies"
    - "deanonymisation of clients in bitcoin p2p network"
    - "bitcoin over tor isn t a good idea"
    - "spy vs spy rumor source obfuscation"
    - "a robust information source estimator with sparse observations"
    - "locating the source of diffusion in large scale networks"
    - "max product for maximum weight matching convergence correctness and lp duality"

Connected through hyperedge HE-2 (induced by source paper "hiding the rumor source"):
  with members:
    - "infection spreading and source identification a hide and seek game"
    - "rumor spreading and source identification a hide and seek game"
    - "riposte an anonymous messaging system handling millions of users"
    - "how to identify an infection source with limited observations"
    - "spy vs spy rumor source obfuscation"
    - "a robust information source estimator with sparse observations"
    - "locating the source of diffusion in large scale networks"
    - "the anatomy of the facebook social graph"

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)