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: "tracking group evolution in social networks"
  Abstract: Easy access and vast amount of data, especially from long period of time, allows to divide social network into timeframes and create temporal social network. Such network enables to analyse its dynamics. One aspect of the dynamics is analysis of social communities evolution, i.e., how particular group changes over time. To do so, the complete group evolution history is needed. That is why in this paper the new method for group evolution extraction called GED is presented.

Connected through hyperedge HE-1 (induced by source paper "analysis of group evolution prediction in complex networks"):
  with members:
    - "a comparative study of different approaches for tracking communities in evolving social networks"
    - "community discovery in dynamic networks a survey"
    - "wordnet2vec corpora agnostic word vectorization method"
    - "predicting community evolution in social networks"
    - "estimating continuous distributions in bayesian classifiers"
    - "different approaches to community evolution prediction in blogosphere"
    - "ged the method for group evolution discovery in social networks"
    - "identification of group changes in blogosphere"

Connected through hyperedge HE-2 (induced by source paper "a method for group extraction and analysis in multilayer social networks"):
  with members:
    - "group evolution discovery in social networks"
    - "estimating continuous distributions in bayesian classifiers"
    - "analysis of neighbourhoods in multi layered dynamic social networks"
    - "low distortion inference of latent similarities from a multiplex social network"
    - "a degree centrality in multi layered social network"
    - "shortest path discovery in the multi layered social network"
    - "exposing multi relational networks to single relational network analysis algorithms"
    - "social networks that matter twitter under the microscope"

Connected through hyperedge HE-3 (induced by source paper "ged the method for group evolution discovery in social networks"):
  with members:
    - "group evolution discovery in social networks"
    - "multidimensional social network in the social recommender system"
    - "social networks that matter twitter under the microscope"

Connected through hyperedge HE-4 (induced by source paper "analysis of social group dynamics"):
  with members:
    - "social networks that matter twitter under the microscope"

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)