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: "large scale analysis of counseling conversations an application of natural language processing to mental health"
  Abstract: Mental illness is one of the most pressing public health issues of our time. While counseling and psychotherapy can be effective treatments, our knowledge about how to conduct successful counseling conversations has been limited due to lack of large-scale data with labeled outcomes of the conversations. In this paper, we present a large-scale, quantitative study on the discourse of text-message-based counseling conversations. We develop a set of novel computational discourse analysis methods to measure how various linguistic aspects of conversations are correlated with conversation outcomes. Applying techniques such as sequence-based conversation models, language model comparisons, message clustering, and psycholinguistics-inspired word frequency analyses, we discover actionable conversation strategies that are associated with better conversation outcomes.

Connected through hyperedge HE-1 (induced by source paper "trouble on the horizon forecasting the derailment of online conversations as they develop"):
  with members:
    - "something s brewing early prediction of controversy causing posts from discussion features"
    - "forecasting the presence and intensity of hostility on instagram using linguistic and social features"
    - "the effect of extremist violence on hateful speech online"
    - "deep contextualized word representations"
    - "community interaction and conflict on the web"
    - "neural approaches to conversational ai"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "wikiconv a corpus of the complete conversational history of a large online collaborative community"

Connected through hyperedge HE-2 (induced by source paper "finding your voice the linguistic development of mental health counselors"):
  with members:
    - "conversations gone awry detecting early signs of conversational failure"
    - "winning on the merits the joint effects of content and style on debate outcomes"
    - "depression and self harm risk assessment in online forums"
    - "the social dynamics of language change in online networks"
    - "conversational markers of constructive discussions"
    - "conversational flow in oxford style debates"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "computational sociolinguistics a survey"

Connected through hyperedge HE-3 (induced by source paper "conversation model fine tuning for classifying client utterances in counseling dialogues"):
  with members:
    - "a hierarchical latent structure for variational conversation modeling"
    - "universal language model fine tuning for text classification"
    - "regularizing and optimizing lstm language models"
    - "depression and self harm risk assessment in online forums"
    - "tying word vectors and word classifiers a loss framework for language modeling"
    - "unsupervised pretraining for sequence to sequence learning"
    - "a hierarchical latent variable encoder decoder model for generating dialogues"
    - "building end to end dialogue systems using generative hierarchical neural network models"

Connected through hyperedge HE-4 (induced by source paper "avec 2019 workshop and challenge state of mind detecting depression with ai and cross cultural affect recognition"):
  with members:
    - "sewa db a rich database for audio visual emotion and sentiment research in the wild"
    - "deep affect prediction in the wild aff wild database and challenge deep architectures and beyond"
    - "on many to many mapping between concordance correlation coefficient and mean square error"
    - "topic modeling based multi modal depression detection"
    - "avec 2016 depression mood and emotion recognition workshop and challenge"
    - "densely connected convolutional networks"
    - "openxbow introducing the passau open source crossmodal bag of words toolkit"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-5 (induced by source paper "modeling psychotherapy dialogues with kernelized hashcode representations a nonparametric information theoretic approach"):
  with members:
    - "learning matching models with weak supervision for response selection in retrieval based chatbots"
    - "unsupervised discrete sentence representation learning for interpretable neural dialog generation"
    - "decoupling strategy and generation in negotiation dialogues"
    - "a hierarchical latent structure for variational conversation modeling"
    - "generating informative and diverse conversational responses via adversarial information maximization"
    - "kernelized hashcode representations for relation extraction"
    - "generating high quality and informative conversation responses with sequence to sequence models"
    - "towards an automatic turing test learning to evaluate dialogue responses"

Connected through hyperedge HE-6 (induced by source paper "measuring depression symptom severity from spoken language and 3d facial expressions"):
  with members:
    - "deep contextualized word representations"
    - "word embeddings quantify 100 years of gender and ethnic stereotypes"
    - "an empirical evaluation of generic convolutional and recurrent networks for sequence modeling"
    - "topic modeling based multi modal depression detection"
    - "semantics derived automatically from language corpora contain human like biases"
    - "man is to computer programmer as woman is to homemaker debiasing word embeddings"
    - "character aware neural language models"
    - "distributed representations of sentences and documents"

Connected through hyperedge HE-7 (induced by source paper "smhd a large scale resource for exploring online language usage for multiple mental health conditions"):
  with members:
    - "rsdd time temporal annotation of self reported mental health diagnoses"
    - "a short review of ethical challenges in clinical natural language processing"
    - "detecting and explaining crisis"
    - "triaging content severity in online mental health forums"
    - "inferring individual attributes from search engine queries and auxiliary information"
    - "feature studies to inform the classification of depressive symptoms from twitter data for population health"
    - "depression and self harm risk assessment in online forums"
    - "xgboost a scalable tree boosting system"

Connected through hyperedge HE-8 (induced by source paper "positivity bias in customer satisfaction ratings"):
  with members:
    - "deep memory networks for attitude identification"
    - "mining the minds of customers from online chat logs"
    - "effective approaches to attention based neural machine translation"
    - "improved semantic representations from tree structured long short term memory networks"
    - "adam a method for stochastic optimization"
    - "empirical evaluation of gated recurrent neural networks on sequence modeling"
    - "convolutional neural networks for sentence classification"

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)