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: "exploiting all phone media a multidimensional network analysis of phone users sociality"
  Abstract: The growing awareness that human communications and social interactions are assuming a stratified structure, due to the availability of multiple techno-communication channels, including online social networks, mobile phone calls, short messages (SMS) and e-mails, has recently led to the study of multidimensional networks, as a step further the classical Social Network Analysis. A few papers have been dedicated to develop the theoretical framework to deal with such multiplex networks and to analyze some example of multidimensional social networks. In this context we perform the first study of the multiplex mobile social network, gathered from the records of both call and text message activities of millions of users of a large mobile phone operator over a period of 12 weeks. While social networks constructed from mobile phone datasets have drawn great attention in recent years, so far studies have dealt with text message and call data, separately, providing a very partial view of people sociality expressed on phone. Here we analyze how the call and the text message dimensions overlap showing how many information about links and nodes could be lost only accounting for a single layer and how users adopt different media channels to interact with their neighborhood.

Connected through hyperedge HE-1 (induced by source paper "extraction of multilayered social networks from activity data"):
  with members:
    - "multi layered social networks"
    - "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)