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 "political discourse on social media echo chambers gatekeepers and the price of bipartisanship"):
  Abstract: Echo chambers, i.e., situations where one is exposed only to opinions that agree with their own, are an increasing concern for the political discourse in many democratic countries. This paper studies the phenomenon of political echo chambers on social media. We identify the two components in the phenomenon: the opinion that is shared ('echo'), and the place that allows its exposure ('chamber' --- the social network), and examine closely at how these two components interact. We define a production and consumption measure for social-media users, which captures the political leaning of the content shared and received by them. By comparing the two, we find that Twitter users are, to a large degree, exposed to political opinions that agree with their own. We also find that users who try to bridge the echo chambers, by sharing content with diverse leaning, have to pay a 'price of bipartisanship' in terms of their network centrality and content appreciation. In addition, we study the role of 'gatekeepers', users who consume content with diverse leaning but produce partisan content (with a single-sided leaning), in the formation of echo chambers. Finally, we apply these findings to the task of predicting partisans and gatekeepers from social and content features. While partisan users turn out relatively easy to identify, gatekeepers prove to be more challenging.

Includes members:
  Member "balancing information exposure in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "combating fake news a survey on identification and mitigation techniques")
  Member "the effect of collective attention on controversial debates on social media":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "predicting the role of political trolls in social media")
  Member "a long term analysis of polarization on twitter":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ideotrace a framework for ideology tracing with a case study on the 2016 u s presidential election")
  Member "limited individual attention and online virality of low quality information":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "reducing controversy by connecting opposing views":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "vocabulary based method for quantifying controversy in social media")
  Member "quantifying controversy in social media":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "language in our time an empirical analysis of hashtags")
  Member "partisan sharing facebook evidence and societal consequences":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "political discussions in homogeneous and cross cutting communication spaces")

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)