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 "aggregate characterization of user behavior in twitter and analysis of the retweet graph"):
  Abstract: Most previous analysis of Twitter user behavior has focused on individual information cascades and the social followers graph, in which the nodes for two users are connected if one follows the other. We instead study aggregate user behavior and the retweet graph with a focus on quantitative descriptions. We find that the lifetime tweet distribution is a type-II discrete Weibull stemming from a power law hazard function, that the tweet rate distribution, although asymptotically power law, exhibits a lognormal cutoff over finite sample intervals, and that the inter-tweet interval distribution is a power law with exponential cutoff. The retweet graph is small-world and scale-free, like the social graph, but less disassortative and has much stronger clustering. These differences are consistent with it better capturing the real-world social relationships of and trust between users than the social graph. Beyond just understanding and modeling human communication patterns and social networks, applications for alternative, decentralized microblogging systems---both predicting real-word performance and detecting spam---are discussed.

Includes members:
  Member "twitter reciprocal reply networks exhibit assortativity with respect to happiness":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "networks of power analyzing world leaders interactions on social media")
  Member "crowdsourcing attention and productivity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "benford s law a sleeping beauty sleeping in the dirty pages of logarithmic tables")
  Member "correlated dynamics in human printing behavior":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "computational human dynamics")

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)