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 "how polarized have we become a multimodal classification of trump followers and clinton followers"):
  Abstract: Polarization in American politics has been extensively documented and analyzed for decades, and the phenomenon became all the more apparent during the 2016 presidential election, where Trump and Clinton depicted two radically different pictures of America. Inspired by this gaping polarization and the extensive utilization of Twitter during the 2016 presidential campaign, in this paper we take the first step in measuring polarization in social media and we attempt to predict individuals’ Twitter following behavior through analyzing ones’ everyday tweets, profile images and posted pictures. As such, we treat polarization as a classification problem and study to what extent Trump followers and Clinton followers on Twitter can be distinguished, which in turn serves as a metric of polarization in general. We apply LSTM to processing tweet features and we extract visual features using the VGG neural network. Integrating these two sets of features boosts the overall performance. We are able to achieve an accuracy of 69%, suggesting that the high degree of polarization recorded in the literature has started to manifest itself in social media as well.

Includes members:
  Member "a selfie is worth a thousand words mining personal patterns behind user selfie posting behaviours":
    also connected through other hyperedges:
      (none)
  Member "catching fire via likes inferring topic preferences of trump followers on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "catching up with trends the changing landscape of political discussions on twitter in 2014 and 2019")
  Member "using word embeddings in twitter election classification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "vocabulary based method for quantifying controversy in social media")
  Member "do they all look the same deciphering chinese japanese and koreans by fine grained deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "considering race a problem of transfer learning")
  Member "gender politics in the 2016 u s presidential election a computer vision approach":
    also connected through other hyperedges:
      (none)
  Member "actionable and political text classification using word embeddings and lstm":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "viewpoint discovery and understanding in social networks")
  Member "pricing the woman card gender politics between hillary clinton and donald trump":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the great division")
  Member "voting with feet who are leaving hillary clinton and donald trump":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the great division")

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)