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: "cooperative phoneotypes exploring phone based behavioral markers of cooperation"
  Abstract: Cooperation is a fundamental human concept studied across multiple social and biological disciplines. Traditional methods for eliciting an individual's propensity to cooperate have included surveys and laboratory experiments and multiple such studies have connected an individual's cooperation level with her social behavior. We describe a novel approach to model an individual's cooperation level based on her phoneotype i.e. a composite of an individual's traits as observable via a mobile phone. This phone sensing-based method can potentially complement surveys, thus providing a cheaper, faster, automated method for generating insights into cooperation levels of users. Based on a 10-week field study involving 54 participants, we report that: (1) multiple phone-based signals were significantly associated with participant's cooperation attitudes; and (2) combining phone-based signals yielded a predictive model with AUCROC of 0.945 that performed significantly better than a comparable demography-based model at predicting individual cooperation propensities. The results pave the way for individuals and organizations to identify more cooperative peers in personal, social, and commerce related settings.

Connected through hyperedge HE-1 (induced by source paper "what twitter profile and posted images reveal about depression and anxiety"):
  with members:
    - "understanding and measuring psychological stress using social media"
    - "wearing many social hats how different are your different social network personae"
    - "what your facebook profile picture reveals about your personality"
    - "instagram photos reveal predictive markers of depression"
    - "human pose estimation from depth images via inference embedded multi task learning"
    - "greysanatomy vs yankees demographics and hashtag use on twitter"
    - "photo aesthetics ranking network with attributes and content adaptation"
    - "social media image analysis for public health"

Connected through hyperedge HE-2 (induced by source paper "understanding and measuring psychological stress using social media"):
  with members:
    - "what twitter profile and posted images reveal about depression and anxiety"
    - "tensistrength stress and relaxation magnitude detection for social media texts"

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)