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 does market concern derived from the internet affect oil prices"
  Abstract: With the acceleration of oil marketisation and the rapid development of electronic information carriers, external information shocks can be easily and quickly transmitted to the oil market through the Internet. This paper analyses the impact of short- and long-run market concerns, derived from search query volumes in Google for different domains around the oil market on oil volatility using co-integration and the modified EGARCH model. Empirical results suggest there is a long-term equilibrium relationship between oil prices and long-run market concern for oil prices and oil demand. The short-run market concerns for the 2008 financial crisis and the Libyan war convulsion have a significant and asymmetric influence on oil price volatility. This indicates that market concern transmitted through the Internet can strengthen the linkage between oil price changes and external events by influencing the expectation of market traders, and to some extent it can exaggerate the impact of nonfundamental information shocks.

Connected through hyperedge HE-1 (induced by source paper "s mart novel tree based structured learning algorithms applied to tweet entity linking"):
  with members:
    - "tagme on the fly annotation of short text fragments by wikipedia entities"

Connected through hyperedge HE-2 (induced by source paper "altmetrics chapter from beyond bibliometrics harnessing multidimensional indicators of scholarly impact"):
  with members:
    - "tracing scientist s research trends realtimely"
    - "how the scientific community reacts to newly submitted preprints article downloads twitter mentions and citations"
    - "beyond citations scholars visibility on the social web"
    - "altmetrics in the wild using social media to explore scholarly impact"
    - "twitter mood predicts the stock market"
    - "a principal component analysis of 39 scientific impact measures"
    - "analysis of social voting patterns on digg"
    - "scientific citations in wikipedia"

Connected through hyperedge HE-3 (induced by source paper "forecasting of events by tweet data mining"):
  with members:
    - "twitter mood predicts the stock market"
    - "learning concept hierarchies from text corpora using formal concept analysis"

Connected through hyperedge HE-4 (induced by source paper "can twitter predict royal baby s name"):
  with members:
    - "twitter mood predicts the stock market"

Connected through hyperedge HE-5 (induced by source paper "can social microblogging be used to forecast intraday exchange rates"):
  with members:
    - "twitter mood predicts the stock market"

Connected through hyperedge HE-6 (induced by source paper "data mining of the concept end of the world in twitter microblogs"):
  with members:
    - "twitter mood predicts the stock market"

Connected through hyperedge HE-7 (induced by source paper "truthy mapping the spread of astroturf in microblog streams"):
  with members:
    - "twitter mood predicts the stock market"
    - "inferring networks of diffusion and influence"
    - "influence and passivity in social media"
    - "social networks that matter twitter under the microscope"
    - "between conjecture and memento shaping a collective emotional perception of the future"

Connected through hyperedge HE-8 (induced by source paper "twitter mood predicts the stock market"):
  with members:
    - "happiness is assortative in online social networks"
    - "measuring the happiness of large scale written expression songs blogs and presidents"
    - "between conjecture and memento shaping a collective emotional perception of the future"

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)