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: "time varying graphs and social network analysis temporal indicators and metrics"
  Abstract: Most instruments - formalisms, concepts, and metrics - for social networks analysis fail to capture their dynamics. Typical systems exhibit different scales of dynamics, ranging from the fine-grain dynamics of interactions (which recently led researchers to consider temporal versions of distance, connectivity, and related indicators), to the evolution of network properties over longer periods of time. This paper proposes a general approach to study that evolution for both atemporal and temporal indicators, based respectively on sequences of static graphs and sequences of time-varying graphs that cover successive time-windows. All the concepts and indicators, some of which are new, are expressed using a time-varying graph formalism.

Connected through hyperedge HE-1 (induced by source paper "edge disjoint branchings in temporal graphs"):
  with members:
    - "stream graphs and link streams for the modeling of interactions over time"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-2 (induced by source paper "stream graphs and link streams for the modeling of interactions over time"):
  with members:
    - "degree based outlier detection within ip traffic modelled as a link stream"
    - "non altering time scales for aggregation of dynamic networks into series of graphs"
    - "movie rating prediction using content based and link stream features"
    - "motifs in temporal networks"
    - "discovering patterns of interest in ip traffic using cliques in bipartite link streams"
    - "time series analysis of temporal networks"
    - "graphprints towards a graph analytic method for network anomaly detection"
    - "semirings for temporal network analysis"

Connected through hyperedge HE-3 (induced by source paper "efficient processing of reachability and time based path queries in a temporal graph"):
  with members:
    - "dagger a scalable index for reachability queries in large dynamic graphs"

Connected through hyperedge HE-4 (induced by source paper "tempus fugit the impact of time in knowledge mobilization networks"):
  with members:
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-5 (induced by source paper "systems for near real time analysis of large scale dynamic graphs"):
  with members:
    - "on the bursty evolution of online social networks"
    - "blinkdb queries with bounded errors and bounded response times on very large data"
    - "efficient subgraph matching on billion node graphs"
    - "an empirical study and analysis of the dynamic load balancing techniques used in parallel computing systems"

Connected through hyperedge HE-6 (induced by source paper "temporal graph traversals definitions algorithms and applications"):
  with members:
    - "on graph deltas for historical queries"
    - "exploration of periodically varying graphs"

Connected through hyperedge HE-7 (induced by source paper "characterizing and evaluation temporal properties of real and synthetic datasets for dtn"):
  with members:
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-8 (induced by source paper "rooting opinions in the minds a cognitive model and a formal account of opinions and their dynamics"):
  with members:
    - "dynamic monopolies in colored tori"
    - "emergence through selection the evolution of a scientific challenge"
    - "time varying graphs and dynamic networks"
    - "multicolored dynamos on toroidal meshes"
    - "selection in scientific networks"

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)