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 "political text scaling meets computational semantics"):
  Abstract: During the last fifteen years, text scaling approaches have become a central element for the text-as-data community. However, they are based on the assumption that latent positions can be captured just by modeling word-frequency information from the different documents under study. We challenge this by presenting a new semantically aware unsupervised scaling algorithm, SemScale, which relies upon distributional representations of the documents under study. We conduct an extensive quantitative analysis over a collection of speeches from the European Parliament in five different languages and from two different legislations, in order to understand whether a) an approach that is aware of semantics would better capture known underlying political dimensions compared to a frequency-based scaling method, b) such positioning correlates in particular with a specific subset of linguistic traits, compared to the use of the entire text, and c) these findings hold across different languages. To support further research on this new branch of text scaling approaches, we release the employed dataset and evaluation setting, an easy-to-use online demo, and a Python implementation of SemScale.

Includes members:
  Member "baseline needs more love on simple word embedding based models and associated pooling mechanisms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "meta embeddings based on self attention")
  Member "detecting policy preferences and dynamics in the un general debate with neural word embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "discursive landscapes and unsupervised topic modeling in ir a validation of text as data approaches through a new corpus of un security council speeches on afghanistan")
  Member "deep joint entity disambiguation with local neural attention":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "improving entity linking by modeling latent entity type information")
  Member "enriching word vectors with subword information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "distributed representations of words and phrases and their compositionality":
    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")

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)