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: "analysis of neighbourhoods in multi layered dynamic social networks"
  Abstract: Abstract Social networks existing among employees, customers or other types of users of various IT systems have become one of the research areas of growing importance. Data about people and their interactions that exist in social media, provides information about many different types of relationships within one network. Analysing this data one can obtain knowledge not only about the structure and characteristics of the network but it also enables to understand the semantic of human relations. Each social network consists of nodes – social entities and edges linking pairs of nodes. In regular, one-layered networks, two nodes – i.e. people are connected with a single edge whereas in the multi-layered social networks, there may be many links of different types for a pair of nodes. Most of the methods used for social network analysis (SNA) may be applied only to one-layered networks. Thus, some new structural measures for multi-layered social networks are proposed in the paper. This study focuses on definitio...

Connected through hyperedge HE-1 (induced by source paper "principled multilayer network embedding"):
  with members:
    - "spectral clustering methods for multiplex networks"
    - "fast warped graph embedding unifying framework and one click algorithm"
    - "name disambiguation in anonymized graphs using network embedding"
    - "community detection link prediction and layer interdependence in multilayer networks"
    - "multilayer spectral graph clustering via convex layer aggregation"
    - "higher order organization of complex networks"
    - "node2vec scalable feature learning for networks"
    - "clustering network layers with the strata multilayer stochastic block model"

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"
    - "tracking group evolution in 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 "a picture is worth a thousand words an empirical study on the influence of content visibility on diffusion processes within a virtual world"):
  with members:
    - "spreading processes in multilayer networks"
    - "knowledge workers collaborative learning behavior modeling in an organizational social network"
    - "knowledge acquisition from social platforms based on network distributions fitting"
    - "model of multilayer knowledge diffusion for competence development in an organization"
    - "seed selection for spread of influence in social networks temporal vs static approach"
    - "extraction of multilayered social networks from activity data"
    - "multi layered social networks"
    - "the online laboratory conducting experiments in a real labor market"

Connected through hyperedge HE-4 (induced by source paper "extraction of multilayered social networks from activity data"):
  with members:
    - "exploiting all phone media a multidimensional network analysis of phone users sociality"
    - "multi layered social networks"
    - "low distortion inference of latent similarities from a multiplex social network"
    - "a degree centrality in multi layered social network"
    - "a classification for community discovery methods in complex networks"
    - "shortest path discovery in the multi layered social network"
    - "multidimensional social network in the social recommender system"
    - "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)