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: "social networking by proxy a case study of catster dogster and hamsterster"
  Abstract: The proliferation of online social networks in the last decadehas not stopped short of pets, and many di erent onlineplatforms now exist catering to owners of various pets suchas cats and dogs. These online pet social networks providea unique opportunity to study an online social network inwhich a single user manages multiple user pro les, i.e. onefor each pet they own. These types of multi-pro le net-works allow us to investigate two questions: (1) What isthe relationship between the pet-level and human-level net-work, and (2) what is the relationship between friendshiplinks and family ties? Concretely, we study the online petsocial networks Catster, Dogster and Hamsterster, the rsttwo of which are the two largest online pet networks in ex-istence. We show how the networks on the two levels inter-act, and perform experiments to nd out whether knowledgeabout friendships on a pro le-level alone can be used to pre-dict which users are behind which pro le. In order to doso, we introduce the concept of multi-pro le social network,extend a previously de ned spectral test of diagonality tomulti-pro le networks, de ne two new homophily measuresfor multi-pro le social networks, perform a two-level socialnetwork analysis, and present an algorithm for predictingwhether two pro les were created by the same user. Asa result, we are able to predict with very high precisionwhether two pro les were created by a same user. Our workis thus relevant for the analysis of other online communitiesin which users may use multiple pro les.

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)