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: "multi layered social networks"
  Abstract: It is quite obvious that in the real world, more than one kind of relationship can exist between two actors and that those ties can be so intertwined that it is impossible to analyse them separately [Fienberg 85], [Minor 83], [Szell 10]. Social networks with more than one type of relation are not a completely new concept [Wasserman 94] but they were analysed mainly at the small scale, e.g. in [McPherson 01], [Padgett 93], and [Entwisle 07]. Just like in the case of regular single-layered social network there is no widely accepted definition or even common name. At the beginning such networks have been called multiplex network [Haythornthwaite 99], [Monge 03]. The term is derived from communications theory which defines multiplex as combining multiple signals into one in such way that it is possible to separate them if needed [Hamill 06]. Recently, the area of multi-layered social network has started attracting more and more attention in research conducted within different domains [Kazienko 11a], [Szell 10], [Rodriguez 07], [Rodriguez 09], and the meaning of multiplex network has expanded and covers not only social relationships but any kind of connection, e.g. based on geography, occupation, kinship, hobbies, etc. [Abraham 12]. This essay aims to summarize existing knowledge about one concept which has many different names i.e. the concept of Multi-layered Social Network also known as Layered social network, Multi-relational social network, Multidimensional social network, Multiplex social network

Connected through hyperedge HE-1 (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"
    - "analysis of neighbourhoods in multi layered dynamic social networks"
    - "the online laboratory conducting experiments in a real labor market"

Connected through hyperedge HE-2 (induced by source paper "a multilayer approach to multiplexity and link prediction in online geo social networks"):
  with members:
    - "keep your friends close and your facebook friends closer a multiplex network approach to the analysis of offline and online social ties"
    - "measuring large scale social networks with high resolution"
    - "social bootstrapping how pinterest and last fm social communities benefit by borrowing links from facebook"
    - "supervised random walks predicting and recommending links in social networks"

Connected through hyperedge HE-3 (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"
    - "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"
    - "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)