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: "to follow or not to follow analyzing the growth patterns of the trumpists on twitter"
  Abstract: In this paper, we analyze the growth patterns of Donald Trump's followers (Trumpists, henceforth) on Twitter. We first construct a random walk model with a time trend to study the growth trend and the effects of public debates. We then analyze the relationship between Trump's activity on Twitter and the growth of his followers. Thirdly, we analyze the effects of such controversial events as calling for Muslim ban and his 'schlonged' remark.

Connected through hyperedge HE-1 (induced by source paper "tactics and tallies a study of the 2016 u s presidential campaign using twitter likes"):
  with members:
    - "deciphering the 2016 u s presidential campaign in the twitter sphere a comparison of the trumpists and clintonists"

Connected through hyperedge HE-2 (induced by source paper "gender politics in the 2016 u s presidential election a computer vision approach"):
  with members:
    - "catching fire via likes inferring topic preferences of trump followers on twitter"
    - "voting with feet who are leaving hillary clinton and donald trump"
    - "deciphering the 2016 u s presidential campaign in the twitter sphere a comparison of the trumpists and clintonists"
    - "ms celeb 1m a dataset and benchmark for large scale face recognition"
    - "multi view face detection using deep convolutional neural networks"
    - "deep residual learning for image recognition"
    - "a century of portraits a visual historical record of american high school yearbooks"
    - "very deep convolutional networks for large scale image recognition"

Connected through hyperedge HE-3 (induced by source paper "will sanders supporters jump ship for trump fine grained analysis of twitter followers"):
  with members:
    - "catching fire via likes inferring topic preferences of trump followers on twitter"
    - "pricing the woman card gender politics between hillary clinton and donald trump"
    - "voting with feet who are leaving hillary clinton and donald trump"
    - "deciphering the 2016 u s presidential campaign in the twitter sphere a comparison of the trumpists and clintonists"
    - "a century of portraits a visual historical record of american high school yearbooks"

Connected through hyperedge HE-4 (induced by source paper "tactics and tallies inferring voter preferences in the 2016 u s presidential primaries using sparse learning"):
  with members:
    - "catching fire via likes inferring topic preferences of trump followers on twitter"
    - "voting with feet who are leaving hillary clinton and donald trump"
    - "deciphering the 2016 u s presidential campaign in the twitter sphere a comparison of the trumpists and clintonists"

Connected through hyperedge HE-5 (induced by source paper "pricing the woman card gender politics between hillary clinton and donald trump"):
  with members:
    - "catching fire via likes inferring topic preferences of trump followers on twitter"
    - "deciphering the 2016 u s presidential campaign in the twitter sphere a comparison of the trumpists and clintonists"
    - "a century of portraits a visual historical record of american high school yearbooks"

Connected through hyperedge HE-6 (induced by source paper "voting with feet who are leaving hillary clinton and donald trump"):
  with members:
    - "catching fire via likes inferring topic preferences of trump followers on twitter"
    - "deciphering the 2016 u s presidential campaign in the twitter sphere a comparison of the trumpists and clintonists"

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)