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 "quantifying the dynamics of topical fluctuations in language"):
  Abstract: The availability of large diachronic corpora has provided the impetus for a growing body of quantitative research on language evolution and meaning change. The central quantities in this research are token frequencies of linguistic elements in the texts, with changes in frequency taken to reflect the popularity or selective fitness of an element. However, corpus frequencies may change for a wide variety of reasons, including purely random sampling effects, or because corpora are composed of contemporary media and fiction texts within which the underlying topics ebb and flow with cultural and socio-political trends. In this work, we introduce a computationally simple model for controlling for topical fluctuations in corpora - the topical-cultural advection model - and demonstrate how it provides a robust baseline of variability in word frequency changes over time. We validate the model on a diachronic corpus spanning two centuries, and a carefully-controlled artificial language change scenario, and then use it to correct for topical fluctuations in historical time series. Finally, we show that the model can be used to show that emergence of new words typically corresponds with the rise of a trending topic. This suggests that some lexical innovations occur due to growing communicative need in a subspace of the lexicon, and that the topical-cultural advection model can be used to quantify this.

Includes members:
  Member "german in flux detecting metaphoric change via word entropy":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simulating lexical semantic change from sense annotated data")
  Member "population size predicts lexical diversity but so does the mean sea level why it is important to correctly account for the structure of temporal data":
    also connected through other hyperedges:
      (none)
  Member "cultural shift or linguistic drift comparing two computational measures of semantic change":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "simulating lexical semantic change from sense annotated data")
  Member "testing apsyn against vector cosine on similarity estimation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "measuring thematic fit with distributional feature overlap")
  Member "diachronic word embeddings reveal statistical laws of semantic change":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a framework for the computational linguistic analysis of dehumanization")
  Member "statistically significant detection of linguistic change":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a framework for the computational linguistic analysis of dehumanization")
  Member "a model of grassroots changes in linguistic systems":
    also connected through other hyperedges:
      (none)
  Member "temporal analysis of language through neural language models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capturing evolution in word usage just add more clusters")

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)