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: "surviving an eternal september how an online community managed a surge of newcomers"
  Abstract: We present a qualitative analysis of interviews with participants in the NoSleep community within Reddit where millions of fans and writers of horror fiction congregate. We explore how the community handled a massive, sudden, and sustained increase in new members. Although existing theory and stories like Usenet's infamous "Eternal September" suggest that large influxes of newcomers can hurt online communities, our interviews suggest that NoSleep survived without major incident. We propose that three features of NoSleep allowed it to manage the rapid influx of newcomers gracefully: (1) an active and well-coordinated group of administrators, (2) a shared sense of community which facilitated community moderation, and (3) technological systems that mitigated norm violations. We also point to several important trade-offs and limitations.

Connected through hyperedge HE-1 (induced by source paper "keeping community in the loop understanding wikipedia stakeholder values for machine learning based systems"):
  with members:
    - "the frontiers of fairness in machine learning"
    - "an empirical study of rich subgroup fairness for machine learning"
    - "fairness and accountability design needs for algorithmic support in high stakes public sector decision making"
    - "on fairness and calibration"
    - "network dissection quantifying interpretability of deep visual representations"
    - "explanation in artificial intelligence insights from the social sciences"
    - "operationalizing conflict and cooperation between automated software agents in wikipedia a replication and expansion of even good bots fight"
    - "algorithmic decision making and the cost of fairness"

Connected through hyperedge HE-2 (induced by source paper "to act or react investigating proactive strategies for online community moderation"):
  with members:
    - "the effect of extremist violence on hateful speech online"
    - "on the origins of memes by means of fringe web communities"
    - "automated hate speech detection and the problem of offensive language"
    - "measuring offensive speech in online political discourse"
    - "online political discourse in the trump era"
    - "social resilience in online communities the autopsy of friendster"

Connected through hyperedge HE-3 (induced by source paper "she s reddit a source of statistically significant gendered interest information"):
  with members:
    - "latent structure in collaboration the case of reddit r place"
    - "caveat emptor computational social science large scale missing data in a widely published reddit corpus"
    - "identifying the social signals that drive online discussions a case study of reddit communities"
    - "consumers and curators browsing and voting patterns on reddit"
    - "gender based violence in 140 characters or fewer a bigdata case study of twitter"

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)