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: "how to ask for technical help evidence based guidelines for writing questions on stack overflow"
  Abstract: Abstract   Context  The success of Stack Overflow and other community-based question-and-answer (Q&A) sites depends mainly on the will of their members to answer others’ questions. In fact, when formulating requests on Q&A sites, we are not simply seeking for information. Instead, we are also asking for other people's help and feedback. Understanding the dynamics of the participation in Q&A communities is essential to improve the value of crowdsourced knowledge.    Objective  In this paper, we investigate how information seekers can increase the chance of eliciting a successful answer to their questions on Stack Overflow by focusing on the following actionable factors: affect, presentation quality, and time.    Method  We develop a conceptual framework of factors potentially influencing the success of questions in Stack Overflow. We quantitatively analyze a set of over 87 K questions from the official Stack Overflow dump to assess the impact of actionable factors on the success of technical requests. The information seeker reputation is included as a control factor. Furthermore, to understand the role played by affective states in the success of questions, we qualitatively analyze questions containing positive and negative emotions. Finally, a survey is conducted to understand how Stack Overflow users perceive the guideline suggestions for writing questions.    Results  We found that regardless of user reputation, successful questions are short, contain code snippets, and do not abuse with uppercase characters. As regards affect, successful questions adopt a neutral emotional style.    Conclusion  We provide evidence-based guidelines for writing effective questions on Stack Overflow that software engineers can follow to increase the chance of getting technical help. As for the role of affect, we empirically confirmed community guidelines that suggest avoiding rudeness in question writing.

Connected through hyperedge HE-1 (induced by source paper "contextual documentation referencing on stack overflow"):
  with members:
    - "9 6 million links in source code comments purpose evolution and decay"
    - "sotorrent reconstructing and analyzing the evolution of stack overflow posts"
    - "usage and attribution of stack overflow code snippets in github projects"

Connected through hyperedge HE-2 (induced by source paper "benefitting from the grey literature in software engineering research"):
  with members:
    - "cut to the chase revisiting the relevance of software engineering research"
    - "monorepos a multivocal literature review"

Connected through hyperedge HE-3 (induced by source paper "an empirical study on the characteristics of question answering process on developer forums"):
  with members:
    - "an empirical assessment of best answer prediction models in technical q a sites"
    - "an empirical study of obsolete answers on stack overflow"

Connected through hyperedge HE-4 (induced by source paper "an empirical assessment of best answer prediction models in technical q a sites"):
  with members:
    - "tuning for software analytics"

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"
    - "bootstrapping a lexicon for emotional arousal in software engineering"
    - "emotxt a toolkit for emotion recognition from text"
    - "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 "investigating crowd creativity in online music communities"):
  with members:
    - "collaboration success factors in an online music community"
    - "gamification a game changer for managing technical debt a design study"
    - "mining communication data in a music community a preliminary analysis"
    - "the remixing dilemma the trade off between generativity and originality"

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"
    - "bootstrapping a lexicon for emotional arousal in software engineering"
    - "emotxt a toolkit for emotion recognition from text"
    - "mining valence arousal and dominance possibilities for detecting burnout and productivity"

Connected through hyperedge HE-8 (induced by source paper "on developers personality in large scale distributed projects the case of the apache ecosystem"):
  with members:
    - "establishing personal trust based connections in distributed teams"
    - "sentiment polarity detection for software development"
    - "a preliminary analysis on the effects of propensity to trust in distributed software development"

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.CY(Computers and Society)