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: "asking too much the rhetorical role of questions in political discourse"
  Abstract: Questions play a prominent role in social interactions, performing rhetorical functions that go beyond that of simple informational exchange. The surface form of a question can signal the intention and background of the person asking it, as well as the nature of their relation with the interlocutor. While the informational nature of questions has been extensively examined in the context of question-answering applications, their rhetorical aspects have been largely understudied. #R##N#In this work we introduce an unsupervised methodology for extracting surface motifs that recur in questions, and for grouping them according to their latent rhetorical role. By applying this framework to the setting of question sessions in the UK parliament, we show that the resulting typology encodes key aspects of the political discourse---such as the bifurcation in questioning behavior between government and opposition parties---and reveals new insights into the effects of a legislator's tenure and political career ambitions.

Connected through hyperedge HE-1 (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"
    - "argument strength is in the eye of the beholder audience effects in persuasion"
    - "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-2 (induced by source paper "a review on dyadic conversation visualizations purposes data lens of analysis"):
  with members:
    - "towards an automatic turing test learning to evaluate dialogue responses"
    - "neural attention models for sequence classification analysis and application to key term extraction and dialogue act detection"
    - "a survey of available corpora for building data driven dialogue systems"

Connected through hyperedge HE-3 (induced by source paper "conversations gone awry detecting early signs of conversational failure"):
  with members:
    - "automated hate speech detection and the problem of offensive language"
    - "measuring gamergate a tale of hate sexism and bullying"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "interpreting neural networks to improve politeness comprehension"
    - "a piece of my mind a sentiment analysis approach for online dispute detection"
    - "ex machina personal attacks seen at scale"
    - "conversational markers of constructive discussions"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"

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)