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: "are friends overrated a study for the social news aggregator digg com"
  Abstract: The key feature of online social networks (OSN) is the ability of users to become active, make friends and interact via comments, videos or messages with those around them. This social interaction is typically perceived as critical to the proper functioning of these platforms; therefore, a significant share of OSN research in the recent past has investigated the characteristics and importance of these social links, studying the networks' friendship relations through their topological properties, the structure of the resulting communities and identifying the role and importance of individual members within these networks. In this paper, we present results from a multi-year study of the online social network Digg.com, indicating that the importance of friends and the friend network in the propagation of information is less than originally perceived. While we do note that users form and maintain a social structure along which information is exchanged, the importance of these links and their contribution is very low: users with even a nearly identical overlap in interests react on average only with a probability of 2% to information propagated and received from friends. Furthermore, in only about 50% of stories that became popular from the entire body of 10 million news we find evidence that the social ties among users were a critical ingredient to the successful spread. Our findings indicate the presence of previously unconsidered factors, the temporal alignment between user activities and the existence of additional logical relationships beyond the topology of the social graph, that are able to drive and steer the dynamics of such OSNs.

Connected through hyperedge HE-1 (induced by source paper "complex contagions a decade in review"):
  with members:
    - "bots as virtual confederates design and ethics"
    - "multi stage complex contagions"
    - "virality prediction and community structure in social networks"
    - "the role of social networks in information diffusion"
    - "social influence in social advertising evidence from field experiments"
    - "modeling the adoption of innovations in the presence of geographic and media influences"

Connected through hyperedge HE-2 (induced by source paper "are human interactivity times lognormal"):
  with members:
    - "social resilience in online communities the autopsy of friendster"
    - "human dynamics revealed through web analytics"

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)