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: "how to identify an infection source with limited observations"
  Abstract: A rumor spreading in a social network or a disease propagating in a community can be modeled as an infection spreading in a network. Finding the infection source is a challenging problem, which is made more difficult in many applications where we have access only to a limited set of observations. We consider the problem of estimating an infection source for a Susceptible-Infected model, in which not all infected nodes can be observed. When the network is a tree, we show that an estimator for the source node associated with the most likely infection path that yields the limited observations is given by a Jordan center, i.e., a node with minimum distance to the set of observed infected nodes. We also propose approximate source estimators for general networks. Simulation results on various synthetic networks and real world networks suggest that our estimators perform better than distance, closeness, and betweenness centrality based heuristics .

Connected through hyperedge HE-1 (induced by source paper "approximate identification of the optimal epidemic source in complex networks"):
  with members:
    - "the spread of low credibility content by social bots"
    - "dandelion redesigning the bitcoin network for anonymity"
    - "detection and analysis of 2016 us presidential election related rumors on twitter"
    - "the spread of fake news by social bots"
    - "multiple infection sources identification with provable guarantees"
    - "identification of patient zero in static and temporal networks robustness and limitations"
    - "information source detection in the sir model a sample path based approach"
    - "social structure of facebook networks"

Connected through hyperedge HE-2 (induced by source paper "information source detection with limited time knowledge"):
  with members:
    - "on the universality of jordan centers for estimating infection sources in tree networks"
    - "estimating infection sources in networks using partial timestamps"
    - "catch em all locating multiple diffusion sources in networks with partial observations"
    - "multiple infection sources identification with provable guarantees"
    - "hiding the rumor source"
    - "a robust information source estimator with sparse observations"
    - "information source detection in the sir model a sample path based approach"
    - "locating the source of diffusion in large scale networks"

Connected through hyperedge HE-3 (induced by source paper "network topology inference using information cascades with limited statistical knowledge"):
  with members:
    - "estimating infection sources in networks using partial timestamps"
    - "back to the source an online approach for sensor placement and source localization"
    - "network topology inference from spectral templates"
    - "infection spreading and source identification a hide and seek game"
    - "robust decentralized detection and social learning in tandem networks"
    - "whose opinion to follow in multihypothesis social learning a large deviations perspective"
    - "learning laplacian matrix in smooth graph signal representations"
    - "the emerging field of signal processing on graphs extending high dimensional data analysis to networks and other irregular domains"

Connected through hyperedge HE-4 (induced by source paper "estimating infection sources in networks using partial timestamps"):
  with members:
    - "optimal localization of diffusion sources in complex networks"
    - "modeling the propagation of trojan malware in online social networks"
    - "infection spreading and source identification a hide and seek game"
    - "source localization in networks trees and beyond"
    - "spy vs spy rumor source obfuscation"
    - "identifying infection sources and regions in large networks"
    - "a robust information source estimator with sparse observations"
    - "finding an infection source under the sis model"

Connected through hyperedge HE-5 (induced by source paper "back to the source an online approach for sensor placement and source localization"):
  with members:
    - "observer placement for source localization the effect of budgets and transmission variance"
    - "back to the past source identification in diffusion networks from partially observed cascades"
    - "identification of source of rumors in social networks with incomplete information"
    - "approximability of the minimum weighted doubly resolving set problem"
    - "a robust information source estimator with sparse observations"
    - "rooting out the rumor culprit from suspects"
    - "information source detection in the sir model a sample path based approach"
    - "locating the source of diffusion in large scale networks"

Connected through hyperedge HE-6 (induced by source paper "on the universality of jordan centers for estimating infection sources in tree networks"):
  with members:
    - "identifying infection sources and regions in large networks"
    - "a robust information source estimator with sparse observations"
    - "rooting out the rumor culprit from suspects"
    - "information source detection in the sir model a sample path based approach"

Connected through hyperedge HE-7 (induced by source paper "infection spreading and source identification a hide and seek game"):
  with members:
    - "on the universality of jordan centers for estimating infection sources in tree networks"
    - "robust decentralized detection and social learning in tandem networks"
    - "whose opinion to follow in multihypothesis social learning a large deviations perspective"
    - "spy vs spy rumor source obfuscation"
    - "graphical evolutionary game for information diffusion over social networks"
    - "evolutionary dynamics of information diffusion over social networks"
    - "identifying infection sources and regions in large networks"
    - "rooting out the rumor culprit from suspects"

Connected through hyperedge HE-8 (induced by source paper "observer placement for source localization the effect of budgets and transmission variance"):
  with members:
    - "identification of source of rumors in social networks with incomplete information"
    - "the behavior of epidemics under bounded susceptibility"
    - "approximability of the minimum weighted doubly resolving set problem"
    - "spy vs spy rumor source obfuscation"
    - "rooting out the rumor culprit from suspects"
    - "information source detection in the sir model a sample path based approach"
    - "locating the source of diffusion in large scale networks"

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)