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: "gender productivity and prestige in computer science faculty hiring networks"
  Abstract: Women are dramatically underrepresented in computer science at all levels in academia and account for just 15% of tenure-track faculty. Understanding the causes of this gender imbalance would inform both policies intended to rectify it and employment decisions by departments and individuals. Progress in this direction, however, is complicated by the complexity and decentralized nature of faculty hiring and the non-independence of hires. Using comprehensive data on both hiring outcomes and scholarly productivity for 2659 tenure-track faculty across 205 Ph.D.-granting departments in North America, we investigate the multi-dimensional nature of gender inequality in computer science faculty hiring through a network model of the hiring process. Overall, we find that hiring outcomes are most directly affected by (i) the relative prestige between hiring and placing institutions and (ii) the scholarly productivity of the candidates. After including these, and other features, the addition of gender did not significantly reduce modeling error. However, gender differences do exist, e.g., in scholarly productivity, postdoctoral training rates, and in career movements up the rankings of universities, suggesting that the effects of gender are indirectly incorporated into hiring decisions through gender's covariates. Furthermore, we find evidence that more highly ranked departments recruit female faculty at higher than expected rates, which appears to inhibit similar efforts by lower ranked departments. These findings illustrate the subtle nature of gender inequality in faculty hiring networks and provide new insights to the underrepresentation of women in computer science.

Connected through hyperedge HE-1 (induced by source paper "pipeline interventions"):
  with members:
    - "the disparate equilibria of algorithmic decision making when individuals invest rationally"
    - "delayed impact of fair machine learning"
    - "downstream effects of affirmative action"
    - "a short term intervention for long term fairness in the labor market"
    - "fairness under composition"
    - "from fair decision making to social equality"
    - "the frontiers of fairness in machine learning"

Connected through hyperedge HE-2 (induced by source paper "discovering archetypes to interpret evolution of individual behavior"):
  with members:
    - "can we count on social media metrics first insights into the active scholarly use of social media"
    - "career transitions and trajectories a case study in computing"
    - "the misleading narrative of the canonical faculty productivity trajectory"
    - "the mythos of model interpretability"
    - "why should i trust you explaining the predictions of any classifier"
    - "from amateurs to connoisseurs modeling the evolution of user expertise through online reviews"
    - "clustering hidden markov models with variational hem"
    - "analysis of computer science communities based on dblp"

Connected through hyperedge HE-3 (induced by source paper "historical comparison of gender inequality in scientific careers across countries and disciplines"):
  with members:
    - "the misleading narrative of the canonical faculty productivity trajectory"
    - "the journal coverage of web of science and scopus a comparative analysis"
    - "quantifying long term scientific impact"
    - "gender differences in research productivity a bibliometric analysis of the italian academic system"
    - "the contribution of star scientists to overall sex differences in research productivity"

Connected through hyperedge HE-4 (induced by source paper "prestige drives epistemic inequality in the diffusion of scientific ideas"):
  with members:
    - "the misleading narrative of the canonical faculty productivity trajectory"
    - "effectiveness of anonymization in double blind review"
    - "tracing the use of practices through networks of collaboration"
    - "can cascades be predicted"

Connected through hyperedge HE-5 (induced by source paper "automatically assembling a full census of an academic field"):
  with members:
    - "the misleading narrative of the canonical faculty productivity trajectory"

Connected through hyperedge HE-6 (induced by source paper "gendered conversation in a social game streaming platform"):
  with members:
    - "it s a man s wikipedia assessing gender inequality in an online encyclopedia"
    - "document embedding with paragraph vectors"
    - "distributed representations of sentences and documents"
    - "gender asymmetries in reality and fiction the bechdel test of social media"
    - "efficient estimation of word representations in vector space"

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.SI(Social and Information Networks)