human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "network assembly of scientific communities of varying size and specificity"):
  Abstract: Abstract   How does the collaboration network of researchers coalesce around a scientific topic? What sort of social restructuring occurs as a new field develops? Previous empirical explorations of these questions have examined the evolution of co-authorship networks associated with several fields of science, each noting a characteristic shift in network structure as fields develop. Historically, however, such studies have tended to rely on manually annotated datasets and therefore only consider a handful of disciplines, calling into question the universality of the observed structural signature. To overcome this limitation and test the robustness of this phenomenon, we use a comprehensive dataset of over 189,000 scientific articles and develop a framework for partitioning articles and their authors into coherent, semantically related groups representing scientific fields of varying size and specificity. We then use the resulting population of fields to study the structure of evolving co-authorship networks. Consistent with earlier findings, we observe a global topological transition as the co-authorship networks coalesce from a disjointed aggregate into a dense giant connected component that dominates the network. We validate these results using a separate, complimentary corpus of scientific articles, and, overall, we find that the previously reported characteristic structural evolution of a scientific field's associated co-authorship network is robust across a large number of scientific fields of varying size, scope, and specificity. Additionally, the framework developed in this study may be used in other scientometric contexts in order to extend studies to compare across a larger range of scientific disciplines.

Includes members:
  Member "arxiv e prints and the journal of record an analysis of roles and relationships":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "inferring the causal effect of journals on citations")
  Member "the author topic model for authors and documents":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "discriminative topic mining via category name guided text embedding")
  Member "mapping subsets of scholarly information":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hep th")

Question: Please tell me which class the source paper 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)