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: "co evolutionary dynamics in social networks a case study of twitter"
  Abstract: Complex networks often exhibit co-evolutionary dynamics, meaning that the network topology and the state of nodes or links are coupled, affecting each other in overlapping time scales. We focus on the co-evolutionary dynamics of online social networks, and on Twitter in particular. Monitoring the activity of thousands of Twitter users in real-time, and tracking their followers and tweets/retweets, we propose a method to infer new retweet-driven follower relations. The formation of such relations is much more likely than the exogenous creation of new followers in the absence of any retweets. We identify the most significant factors (reciprocity and the number of retweets that a potential new follower receives) and propose a simple probabilistic model of this effect. We also discuss the implications of such co-evolutionary dynamics on the topology and function of a social network.

Connected through hyperedge HE-1 (induced by source paper "optimal containment of epidemics in temporal and adaptive networks"):
  with members:
    - "efficient containment of exact sir markovian processes on networks"
    - "stability of spreading processes over time varying large scale networks"
    - "epidemic processes over adaptive state dependent networks"
    - "decentralized protection strategies against sis epidemics in networks"
    - "an efficient curing policy for epidemics on graphs"
    - "a convex framework for optimal investment on disease awareness in social networks"
    - "optimal vaccine allocation to control epidemic outbreaks in arbitrary networks"
    - "spectral analysis of virus spreading in random geometric networks"

Connected through hyperedge HE-2 (induced by source paper "on the efficiency of the information networks in social media"):
  with members:
    - "back to the past source identification in diffusion networks from partially observed cascades"
    - "the bursty dynamics of the twitter information network"
    - "the role of information diffusion in the evolution of social networks"
    - "the role of social networks in information diffusion"

Connected through hyperedge HE-3 (induced by source paper "coevolve a joint point process model for information diffusion and network co evolution"):
  with members:
    - "modeling adoption and usage of competing products"
    - "the bursty dynamics of the twitter information network"
    - "can cascades be predicted"
    - "the role of information diffusion in the evolution of social networks"
    - "modeling information propagation with survival theory"
    - "subgraph frequencies mapping the empirical and extremal geography of large graph collections"
    - "social dynamics of digg"
    - "uncovering the temporal dynamics of diffusion networks"

Connected through hyperedge HE-4 (induced by source paper "the bursty dynamics of the twitter information network"):
  with members:
    - "can cascades be predicted"
    - "the role of information diffusion in the evolution of social networks"
    - "information diffusion and external influence in networks"
    - "on the interplay between social and topical structure"
    - "supervised random walks predicting and recommending links in social networks"
    - "predicting the popularity of online content"

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)