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: "emotxt a toolkit for emotion recognition from text"
  Abstract: We present EmoTxt, a toolkit for emotion recognition from text, trained and tested on a gold standard of about 9K question, answers, and comments from online interactions. We provide empirical evidence of the performance of EmoTxt. To the best of our knowledge, EmoTxt is the first open-source toolkit supporting both emotion recognition from text and training of custom emotion classification models.

Connected through hyperedge HE-1 (induced by source paper "a large scale in depth analysis of developers personalities in the apache ecosystem"):
  with members:
    - "establishing personal trust based connections in distributed teams"
    - "on developers personality in large scale distributed projects the case of the apache ecosystem"
    - "sentiment polarity detection for software development"
    - "a gold standard for emotion annotation in stack overflow"
    - "natural language or not nlon a package for software engineering text analysis pipeline"
    - "a preliminary analysis on the effects of propensity to trust in distributed software development"
    - "25 tweets to know you a new model to predict personality with social media"
    - "links between the personalities styles and performance in computer programming"

Connected through hyperedge HE-2 (induced by source paper "attention based modeling for emotion detection and classification in textual conversations"):
  with members:
    - "dialoguernn an attentive rnn for emotion detection in conversations"
    - "emotional chatting machine emotional conversation generation with internal and external memory"
    - "word affect intensities"
    - "attention is all you need"
    - "regularizing and optimizing lstm language models"
    - "deep biaffine attention for neural dependency parsing"
    - "pointer sentinel mixture models"
    - "neural machine translation by jointly learning to align and translate"

Connected through hyperedge HE-3 (induced by source paper "emtk the emotion mining toolkit"):
  with members:
    - "sentiment polarity detection for software development"
    - "a gold standard for emotion annotation in stack overflow"
    - "a computational approach to politeness with application to social factors"

Connected through hyperedge HE-4 (induced by source paper "towards understanding and detecting fake reviews in app stores"):
  with members:
    - "a systematic study of online class imbalance learning with concept drift"
    - "the darpa twitter bot challenge"
    - "the rise of social bots"

Connected through hyperedge HE-5 (induced by source paper "a benchmark study on sentiment analysis for software engineering research"):
  with members:
    - "sentiment polarity detection for software development"
    - "how to ask for technical help evidence based guidelines for writing questions on stack overflow"
    - "bootstrapping a lexicon for emotional arousal in software engineering"
    - "mining valence arousal and dominance possibilities for detecting burnout and productivity"
    - "recommending insightful comments for source code using crowdsourced knowledge"
    - "a computational approach to politeness with application to social factors"
    - "machine learning in automated text categorization"
    - "smote synthetic minority over sampling technique"

Connected through hyperedge HE-6 (induced by source paper "how to ask for technical help evidence based guidelines for writing questions on stack overflow"):
  with members:
    - "semeval 2016 task 4 sentiment analysis in twitter"
    - "bootstrapping a lexicon for emotional arousal in software engineering"
    - "recommending insightful comments for source code using crowdsourced knowledge"
    - "do feelings matter on the correlation of affects and the self assessed productivity in software engineering"
    - "how to ask for a favor a case study on the success of altruistic requests"
    - "the role of emotions in contributors activity a case study on the gentoo community"

Connected through hyperedge HE-7 (induced by source paper "a gold standard for emotion annotation in stack overflow"):
  with members:
    - "sentiment polarity detection for software development"
    - "how to ask for technical help evidence based guidelines for writing questions on stack overflow"
    - "bootstrapping a lexicon for emotional arousal in software engineering"
    - "mining valence arousal and dominance possibilities for detecting burnout and productivity"

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.HC(Human-Computer Interaction)