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 "topicality and impact in social media diverse messages focused messengers"):
  Abstract: We have a limited understanding of the factors that make people influential and topics popular in social media. Are users who comment on a variety of matters more likely to achieve high influence than those who stay focused? Do general subjects tend to be more popular than specific ones? Questions like these demand a way to detect the topics hidden behind messages associated with an individual or a keyword, and a gauge of similarity among these topics. Here we develop such an approach to identify clusters of similar hashtags in Twitter by detecting communities in the hashtag co-occurrence network. Then the topical diversity of a user’s interests is quantified by the entropy of her hashtags across different topic clusters. A similar measure is applied to hashtags, based on co-occurring tags. We find that high topical diversity of early adopters or co-occurring tags implies high future popularity of hashtags. In contrast, low diversity helps an individual accumulate social influence. In short, diverse messages and focused messengers are more likely to gain impact.

Includes members:
  Member "can cascades be predicted":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep collaborative embedding for information cascade prediction")
  Member "bigbirds never die understanding social dynamics of emergent hashtag":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "language in our time an empirical analysis of hashtags")
  Member "the role of information diffusion in the evolution of social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the inevitability of online echo chambers")
  Member "clustering memes in social media":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "semantic search of memes on twitter")
  Member "virality prediction and community structure in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "deep collaborative embedding for information cascade prediction")
  Member "real time discovery of dense clusters in highly dynamic graphs identifying real world events in highly dynamic environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mining bursting communities in temporal graphs")
  Member "on the interplay between social and topical structure":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "modeling information diffusion in online social networks with partial differential equations")
  Member "folks in folksonomies social link prediction from shared metadata":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "beautiful and damned combined effect of content quality and social ties on user engagement")

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)