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 "tracking illicit drug dealing and abuse on instagram using multimodal analysis"):
  Abstract: Illicit drug trade via social media sites, especially photo-oriented Instagram, has become a severe problem in recent years. As a result, tracking drug dealing and abuse on Instagram is of interest to law enforcement agencies and public health agencies. In this paper, we propose a novel approach to detecting drug abuse and dealing automatically by utilizing multimodal data on social media. This approach also enables us to identify drug-related posts and analyze the behavior patterns of drug-related user accounts. To better utilize multimodal data on social media, multimodal analysis methods including multitask learning and decision-level fusion are employed in our framework. Experiment results on expertly labeled data have demonstrated the effectiveness of our approach, as well as its scalability and reproducibility over labor-intensive conventional approaches.

Includes members:
  Member "finding street gang members on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "predictive analysis on twitter techniques and applications")
  Member "webly supervised learning of convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning spatiotemporal features via video and text pair discrimination")
  Member "america tweets china a fine grained analysis of the state and individual characteristics regarding attitudes towards china":
    also connected through other hyperedges:
      (none)
  Member "pinterest board recommendation for twitter users":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning semantic specific graph representation for multi label image recognition")
  Member "social media image analysis for public health":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "what twitter profile and posted images reveal about depression and anxiety")
  Member "monitoring potential drug interactions and reactions via network analysis of instagram user timelines":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "going deeper with convolutions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "discrimination aware network pruning for deep model compression")

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)