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: "modeling the adoption of innovations in the presence of geographic and media influences"
  Abstract: While there is a large body of work examining the effects of social network structure on innovation adoption, models to date have lacked considerations of real geography or mass media. In this article, we show these features are crucial to making more accurate predictions of a social contagion and technology adoption at a city-to-city scale. Using data from the adoption of the popular micro-blogging platform, Twitter, we present a model of adoption on a network that places friendships in real geographic space and exposes individuals to mass media influence. We show that homophily both among individuals with similar propensities to adopt a technology and geographic location is critical to reproducing features of real spatiotemporal adoption. Furthermore, we estimate that mass media was responsible for increasing Twitter's user base two to four fold. To reflect this strength, we extend traditional contagion models to include an endogenous mass media agent that responds to those adopting an innovation as well as influencing agents to adopt themselves.

Connected through hyperedge HE-1 (induced by source paper "computational human dynamics"):
  with members:
    - "joint embedding of structure and features via graph convolutional networks"
    - "location occupation and semantics based socioeconomic status inference on twitter"
    - "the temporal event graph"
    - "link transmission centrality in large scale social networks"
    - "socioeconomic dependencies of linguistic patterns in twitter a multivariate analysis"
    - "graph embedding techniques applications and performance a survey"
    - "correlations and dynamics of consumption patterns in social economic networks"
    - "stream graphs and link streams for the modeling of interactions over time"

Connected through hyperedge HE-2 (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"
    - "are friends overrated a study for the social news aggregator digg com"

Connected through hyperedge HE-3 (induced by source paper "nowcasting disaster damage"):
  with members:
    - "the simple rules of social contagion"
    - "performance of social network sensors during hurricane sandy"
    - "the digital evolution of occupy wall street"
    - "the geospatial characteristics of a social movement communication network"
    - "using friends as sensors to detect global scale contagious outbreaks"

Connected through hyperedge HE-4 (induced by source paper "traveling trends social butterflies or frequent fliers"):
  with members:
    - "the digital evolution of occupy wall street"
    - "the geospatial characteristics of a social movement communication network"
    - "clustering memes in social media"
    - "dynamical classes of collective attention in twitter"
    - "truthy mapping the spread of astroturf in microblog streams"
    - "twitter mood predicts the stock market"

Connected through hyperedge HE-5 (induced by source paper "social resilience in online communities the autopsy of friendster"):
  with members:
    - "on the bursty evolution of online social networks"
    - "defining and evaluating network communities based on ground truth"
    - "partisan asymmetries in online political activity"
    - "measuring tie strength in implicit social networks"

Connected through hyperedge HE-6 (induced by source paper "multi stage complex contagions"):
  with members:
    - "social structure of facebook networks"
    - "diffusion in social networks with competing products"
    - "social contagion theory examining dynamic social networks and human behavior"

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)