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 kavanaugh or not to kavanaugh that is the polarizing question"
  Abstract: On October 6, 2018, the US Senate confirmed Brett Kavanaugh with the narrowest margin for a successful confirmation since 1881 and where the senators voted overwhelmingly along party lines. In this paper, we examine whether the political polarization in the Senate is reflected among the general public. To do so, we analyze the views of more than 128 thousand Twitter users. We show that users supporting or opposing Kavanaugh's nomination were generally using divergent hashtags, retweeting different Twitter accounts, and sharing links from different websites. We also examine characterestics of both groups.

Connected through hyperedge HE-1 (induced by source paper "embedding based qualitative analysis of polarization in turkey"):
  with members:
    - "unsupervised user stance detection on twitter"
    - "devam vs tamam 2018 turkish elections"
    - "community interaction and conflict on the web"
    - "word embeddings quantify 100 years of gender and ethnic stereotypes"
    - "semantics derived automatically from language corpora contain human like biases"
    - "enriching word vectors with subword information"
    - "bag of tricks for efficient text classification"
    - "failedrevolutions using twitter to study the antecedents of isis support"

Connected through hyperedge HE-2 (induced by source paper "predicting the topical stance of media and popular twitter users"):
  with members:
    - "unsupervised user stance detection on twitter"
    - "bag of tricks for efficient text classification"
    - "failedrevolutions using twitter to study the antecedents of isis support"
    - "content and network dynamics behind egyptian political polarization on twitter"

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)