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 "an image analysis approach to text analytics based on complex networks"):
  Abstract: Abstract   Text network analysis has received increasing attention as a consequence of its wide range of applications. In this study, we extend a previous work founded on the study of topological features of mesoscopic networks. Here, the geometrical properties of visualized networks are quantified by using several image analysis techniques. Such properties are used to probe the networks characteristics in terms of authorship. It was found that the visual features account for performance similar to that achieved by using topological measurements. Also, we combined and compared the two types of features, topological and geometrical, and the results suggest that the information provided by network topology and image features are complementary.

Includes members:
  Member "representation of texts as complex networks a mesoscopic approach":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "semantic flow in language networks")
  Member "on the calligraphy of books":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "paragraph based representation of texts a complex networks approach")
  Member "using network science and text analytics to produce surveys in a scientific topic":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "science through wikipedia a novel representation of open knowledge through co citation networks")
  Member "concentric network symmetry grasps authors styles in word adjacency networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "using word embeddings to improve the discriminability of co occurrence text networks")
  Member "a complex network approach to stylometry":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "using word embeddings to improve the discriminability of co occurrence text networks")
  Member "probing the topological properties of complex networks modeling short written texts":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "using word embeddings to improve the discriminability of co occurrence text networks")
  Member "authorship attribution through function word adjacency networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "edgenets edge varying graph neural networks")
  Member "structure semantics interplay in complex networks and its effects on the predictability of similarity in texts":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "representation of texts as complex networks a mesoscopic approach")

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.CL(Computation and Language)