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 "argument strength is in the eye of the beholder audience effects in persuasion"):
  Abstract: Americans spend about a third of their time online, with many participating in online conversations on social and political issues. We hypothesize that social media arguments on such issues may be more engaging and persuasive than traditional media summaries, and that particular types of people may be more or less convinced by particular styles of argument, e.g. emotional arguments may resonate with some personalities while factual arguments resonate with others. We report a set of experiments testing at large scale how audience variables interact with argument style to affect the persuasiveness of an argument, an under-researched topic within natural language processing. We show that belief change is affected by personality factors, with conscientious, open and agreeable people being more convinced by emotional arguments.

Includes members:
  Member "getting reliable annotations for sarcasm in online dialogues":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a large self annotated corpus for sarcasm")
  Member "really well apparently bootstrapping improves the performance of sarcasm and nastiness classifiers for online dialogue":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "effectiveness of data driven induction of semantic spaces and traditional classifiers for sarcasm detection")
  Member "creating and characterizing a diverse corpus of sarcasm in dialogue":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "attention based conditioning methods for external knowledge integration")
  Member "learning fine grained knowledge about contingent relations between everyday events":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "detecting everyday scenarios in narrative texts")
  Member "measuring the similarity of sentential arguments in dialogue":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sentence bert sentence embeddings using siamese bert networks")
  Member "learning latent local conversation modes for predicting community endorsement in online discussions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the anatomy of reddit an overview of academic research")
  Member "winning arguments interaction dynamics and persuasion strategies in good faith online discussions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "ten social dimensions of conversations and relationships")
  Member "and that s a fact distinguishing factual and emotional argumentation in online dialogue":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "human misinformation interaction understanding the interdisciplinary approach needed to computationally combat false information")

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)