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: "a piece of my mind a sentiment analysis approach for online dispute detection"
  Abstract: We investigate the novel task of online dispute detection and propose a sentiment analysis solution to the problem: we aim to identify the sequence of sentence-level sentiments expressed during a discussion and to use them as features in a classifier that predicts the DISPUTE/NON-DISPUTE label for the discussion as a whole. We evaluate dispute detection approaches on a newly created corpus of Wikipedia Talk page disputes and find that classifiers that rely on our sentiment tagging features outperform those that do not. The best model achieves a very promising F1 score of 0.78 and an accuracy of 0.80.

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 "discrete argument representation learning for interactive argument pair identification"):
  with members:
    - "unsupervised discrete sentence representation learning for interpretable neural dialog generation"
    - "an efficient framework for learning sentence representations"
    - "automatic summarization of online debates"
    - "attention over attention neural networks for reading comprehension"
    - "best of both worlds transferring knowledge from discriminative learning to a generative visual dialog model"
    - "bilateral multi perspective matching for natural language sentences"
    - "enhanced lstm for natural language inference"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"

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"
    - "asking too much the rhetorical role of questions in political discourse"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "interpreting neural networks to improve politeness comprehension"
    - "ex machina personal attacks seen at scale"
    - "conversational markers of constructive discussions"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"

Connected through hyperedge HE-4 (induced by source paper "wikiconv a corpus of the complete conversational history of a large online collaborative community"):
  with members:
    - "conversations gone awry detecting early signs of conversational failure"
    - "ex machina personal attacks seen at scale"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "a computational approach to politeness with application to social factors"
    - "echoes of power language effects and power differences in social interaction"

Connected through hyperedge HE-5 (induced by source paper "forecasting the presence and intensity of hostility on instagram using linguistic and social features"):
  with members:
    - "automated hate speech detection and the problem of offensive language"
    - "anyone can become a troll causes of trolling behavior in online discussions"
    - "enriching word vectors with subword information"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-6 (induced by source paper "using sentiment representation learning to enhance gender classification for user profiling"):
  with members:
    - "multiview spectral clustering via structured low rank matrix factorization"
    - "how transferable are features in deep neural networks"
    - "efficient estimation of word representations in vector space"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-7 (induced by source paper "anyone can become a troll causes of trolling behavior in online discussions"):
  with members:
    - "conversational markers of constructive discussions"
    - "conversational flow in oxford style debates"
    - "how community feedback shapes user behavior"
    - "characterizing and curating conversation threads expansion focus volume re entry"

Connected through hyperedge HE-8 (induced by source paper "winning on the merits the joint effects of content and style on debate outcomes"):
  with members:
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "crowdsourcing a word emotion association lexicon"
    - "get out the vote determining support or opposition from congressional floor debate transcripts"

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)