human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "limited attention and centrality in social networks"):
  Abstract: How does one find important or influential people in an online social network? Researchers have proposed a variety of centrality measures to identify individuals that are, for example, often visited by a random walk, infected in an epidemic, or receive many messages from friends. Recent research suggests that a social media users' capacity to respond to an incoming message is constrained by their finite attention, which they divide over all incoming information, i.e., information sent by users they follow. We propose a new measure of centrality --- limited-attention version of Bonacich's Alpha-centrality --- that models the effect of limited attention on epidemic diffusion. The new measure describes a process in which nodes broadcast messages to their out-neighbors, but the neighbors' ability to receive the message depends on the number of in-neighbors they have. We evaluate the proposed measure on real-world online social networks and show that it can better reproduce an empirical influence ranking of users than other popular centrality measures.

Includes members:
  Member "google matrix of twitter":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spectral properties of google matrix of wikipedia and other networks")
  Member "rethinking centrality the role of dynamical processes in social network analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "centralities for networks with consumable resources")
  Member "parameterized centrality metric for network analysis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "community detection via katz and eigenvector centrality")
  Member "non conservative diffusion and its application to social network analysis":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "data mining when each data point is a network")
  Member "predicting influential users in online social networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sensing and modeling human behavior using social media and mobile data")
  Member "crowdsourcing attention and productivity":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "benford s law a sleeping beauty sleeping in the dirty pages of logarithmic tables")
  Member "novelty and collective attention":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "modeling the popularity of twitter hashtags with master equations")

Question: Please tell me which class the source paper 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)