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 "contrastive reasons detection and clustering from online polarized debate"):
  Abstract: This work tackles the problem of unsupervised modeling and extraction of the main contrastive sentential reasons conveyed by divergent viewpoints on polarized issues. It proposes a pipeline approach centered around the detection and clustering of phrases, assimilated to argument facets using a novel Phrase Author Interaction Topic-Viewpoint model. The evaluation is based on the informativeness, the relevance and the clustering accuracy of extracted reasons. The pipeline approach shows a significant improvement over state-of-the-art methods in contrastive summarization on online debate datasets.

Includes members:
  Member "argumentation mining in user generated web discourse":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "argulens anatomy of community opinions on usability issues using argumentation models")
  Member "summarizing dialogic arguments from social media":
    also connected through other hyperedges:
      (none)
  Member "stance and sentiment in tweets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dan dual view representation learning for adapting stance classifiers to new domains")
  Member "using summarization to discover argument facets in online idealogical dialog":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "samsum corpus a human annotated dialogue dataset for abstractive summarization")
  Member "scalable topical phrase mining from text corpora":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cate category name guidedword embedding")
  Member "lexrank graph based lexical centrality as salience in text summarization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "generating representative headlines for news stories")

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)