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 "the complexity of social media response statistical evidence for one dimensional engagement signal in twitter"):
  Abstract: Many years after online social networks exceeded our collective attention, social influence is still built on attention capital. Quality is not a prerequisite for viral spreading, yet large diffusion cascades remain the hallmark of a social influencer. Consequently, our exposure to low-quality content and questionable influence is expected to increase. Since the conception of influence maximization frameworks, multiple content performance metrics became available, albeit raising the complexity of influence analysis. In this paper, we examine and consolidate a diverse set of content engagement metrics. The correlations discovered lead us to propose a new, more holistic, one-dimensional engagement signal. We then show it is more predictable than any individual influence predictors previously investigated. Our proposed model achieves strong engagement ranking performance and is the first to explain half of the variance with features available early. We share the detailed numerical workflow to compute the new compound engagement signal. The model is immediately applicable to social media monitoring, influencer identification, campaign engagement forecasting, and curating user feeds.

Includes members:
  Member "scalable privacy compliant virality prediction on twitter":
    also connected through other hyperedges:
      (none)
  Member "limited individual attention and online virality of low quality information":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "quote rts on twitter usage of the new feature for political discourse":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a survey on computational politics")
  Member "good friends bad news affect and virality in twitter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sentiment dynamics in social media news channels")

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)