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 "a picture is worth a thousand words an empirical study on the influence of content visibility on diffusion processes within a virtual world"):
  Abstract: Studying information diffusion and the spread of goods in the real world and in many digital services can be extremely difficult since information about the information flows is challenging to accurately track. How information spreads has commonly been analysed from the perspective of homophily, social influence, and initial seed selection. However, in virtual worlds and virtual economies, the movements of information and goods can be precisely tracked. Therefore, these environments create laboratories for the accurate study of information diffusion characteristics that have been difficult to study in prior research. In this paper, we study how content visibility as well as sender and receiver characteristics, the relationship between them, and the types of multilayer social network layers affect content absorption and diffusion in virtual world. The results show that prior visibility of distributed content is the strongest predictor of content adoption and its further spread across networks. Among other analysed factors, the mechanics of diffusion, content quality, and content adoption by users’ neighbours on the social activity layer had very strong influences on the adoption of new content.

Includes members:
  Member "spreading processes in multilayer networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep learning approach on information diffusion in heterogeneous networks")
  Member "knowledge workers collaborative learning behavior modeling in an organizational social network":
    also connected through other hyperedges:
      (none)
  Member "knowledge acquisition from social platforms based on network distributions fitting":
    also connected through other hyperedges:
      (none)
  Member "model of multilayer knowledge diffusion for competence development in an organization":
    also connected through other hyperedges:
      (none)
  Member "seed selection for spread of influence in social networks temporal vs static approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "evolving influence maximization in evolving networks")
  Member "extraction of multilayered social networks from activity data":
    also connected through other hyperedges:
      (none)
  Member "multi layered social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a multilayer approach to multiplexity and link prediction in online geo social networks")
  Member "analysis of neighbourhoods in multi layered dynamic social networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "principled multilayer network embedding")

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)