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 "inducing affective lexical semantics in historical language"):
  Abstract: The emotional connotation attached to words undergoes language change. In this paper, we aim at estimating the emotion which is associated with a given word in former language stages of English and German. Emotion is represented following the popular Valence-Arousal-Dominance (VAD) annotation scheme. While being more expressive than polarity alone, existing word polarity induction methods are typically not suited for addressing it. To overcome this limitation, we present adaptations of two popular algorithms to VAD. To measure the effectiveness of these methods in diachronic settings, we present two small gold lexicons for historical word emotions which where annotated by scholars with proficiency in the respective language (stage). In contrast to claims in previous work, we find that limiting the training set to words of supposedly stable emotional meaning does in fact decrease performance, rather than boosting it. This contribution thus elaborates algorithmic and experimental results which form the basis of some of our later publications (Buechel et al., 2017; Buechel and Hahn, 2018; Hellrich et al., 2018) yet had to be skipped there, partly for brevity, partly for a change in focus of our work.

Includes members:
  Member "representation mapping a novel approach to generate high quality multi lingual emotion lexicons":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "modeling word emotion in historical language quantity beats supposed stability in seed word selection")
  Member "deep contextualized word representations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "jeseme a website for exploring diachronic changes in word meaning and emotion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "modeling word emotion in historical language quantity beats supposed stability in seed word selection")
  Member "emotion representation mapping for automatic lexicon construction mostly performs on human level":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint emotion label space modelling for affect lexica")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "inducing domain specific sentiment lexicons from unlabeled corpora":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generating word and document embeddings for sentiment analysis")
  Member "ultradense word embeddings by orthogonal transformation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "improving pre trained multilingual models with vocabulary expansion")
  Member "diachronic word embeddings reveal statistical laws of semantic change":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a framework for the computational linguistic analysis of dehumanization")

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)