human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "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.

Connected through hyperedge HE-1 (induced by source paper "what changed your mind the roles of dynamic topics and discourse in argumentation process"):
  with members:
    - "unsupervised dialog structure learning"
    - "what you say and how you say it joint modeling of topics and discourse in microblog conversations"
    - "what gets echoed understanding the pointers in explanations of persuasive arguments"
    - "topic memory networks for short text classification"
    - "a joint model of conversational discourse and latent topics on microblogs"
    - "attentive interaction model modeling changes in view in argumentation"
    - "joint modeling of content and discourse relations in dialogues"
    - "winning on the merits the joint effects of content and style on debate outcomes"

Connected through hyperedge HE-2 (induced by source paper "what gets echoed understanding the pointers in explanations of persuasive arguments"):
  with members:
    - "on human predictions with explanations and predictions of machine learning models a case study on deception detection"
    - "rating reliability and bias in news articles does ai assistance help everyone"
    - "explain yourself leveraging language models for commonsense reasoning"
    - "exploring the role of prior beliefs for argument persuasion"
    - "e snli natural language inference with natural language explanations"
    - "you are no jack kennedy on media selection of highlights from presidential debates"
    - "explanation in artificial intelligence insights from the social sciences"
    - "opennmt open source toolkit for neural machine translation"

Connected through hyperedge HE-3 (induced by source paper "scalable bayesian preference learning for crowds"):
  with members:
    - "bayesian heatmaps probabilistic classification with multiple unreliable information sources"
    - "hybrid mst a hybrid active sampling strategy for pairwise preference aggregation"
    - "finding convincing arguments using scalable bayesian preference learning"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "best worst scaling more reliable than rating scales a case study on sentiment intensity annotation"
    - "distributed bayesian probabilistic matrix factorization"
    - "robust subjective visual property prediction from crowdsourced pairwise labels"
    - "distributed bayesian probabilistic matrix factorization"

Connected through hyperedge HE-4 (induced by source paper "an unsupervised domain independent framework for automated detection of persuasion tactics in text"):
  with members:
    - "event outcome prediction using sentiment analysis and crowd wisdom in microblog feeds"
    - "object sensitive deep reinforcement learning"
    - "transparency and explanation in deep reinforcement learning neural networks"
    - "photorealistic style transfer for videos"
    - "joint embedding of hierarchical categories and entities for concept categorization and dataless classification"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "content based video indexing and retrieval using corr lda"
    - "distributed representations of sentences and documents"

Connected through hyperedge HE-5 (induced by source paper "modeling financial analysts decision making via the pragmatics and semantics of earnings calls"):
  with members:
    - "attentive interaction model modeling changes in view in argumentation"
    - "asking too much the rhetorical role of questions in political discourse"
    - "relnet end to end modeling of entities relations"
    - "volatility prediction using financial disclosures sentiments with word embedding based ir models"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "leverage financial news to predict stock price movements using word embeddings and deep neural networks"
    - "adam a method for stochastic optimization"
    - "distributed representations of sentences and documents"

Connected through hyperedge HE-6 (induced by source paper "persuasion for good towards a personalized persuasive dialogue system for social good"):
  with members:
    - "conversational analysis using utterance level attention based bidirectional recurrent neural networks"
    - "decoupling strategy and generation in negotiation dialogues"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "sentiment adaptive end to end dialog systems"
    - "learning to generate reviews and discovering sentiment"
    - "deal or no deal end to end learning for negotiation dialogues"
    - "enriching word vectors with subword information"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"

Connected through hyperedge HE-7 (induced by source paper "a corpus for modeling user and language effects in argumentation on online debating"):
  with members:
    - "exploring the role of prior beliefs for argument persuasion"
    - "winning on the merits the joint effects of content and style on debate outcomes"
    - "talk it up or play it down un expected correlations between de emphasis and recurrence of discussion points in consequential u s economic policy meetings"
    - "conversational flow in oxford style debates"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "echoes of persuasion the effect of euphony in persuasive communication"
    - "a computational approach to politeness with application to social factors"

Connected through hyperedge HE-8 (induced by source paper "attentive interaction model modeling changes in view in argumentation"):
  with members:
    - "before name calling dynamics and triggers of ad hominem fallacies in web argumentation"
    - "supervised learning of universal sentence representations from natural language inference data"
    - "argument mining with structured svms and rnns"
    - "conversational flow in oxford style debates"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "personalized emphasis framing for persuasive message generation"
    - "a large annotated corpus for learning natural language inference"
    - "on the properties of neural machine translation encoder decoder approaches"

Question: Please tell me which class the center node 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)