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 "network segregation in a model of misinformation and fact checking"):
  Abstract: Misinformation under the form of rumor, hoaxes, and conspiracy theories spreads on social media at alarming rates. One hypothesis is that, since social media are shaped by homophily, belief in misinformation may be more likely to thrive on those social circles that are segregated from the rest of the network. One possible antidote is fact checking which, in some cases, is known to stop rumors from spreading further. However, fact checking may also backfire and reinforce the belief in a hoax. Here we take into account the combination of network segregation, finite memory and attention, and fact-checking efforts. We consider a compartmental model of two interacting epidemic processes over a network that is segregated between gullible and skeptic users. Extensive simulation and mean-field analysis show that a more segregated network facilitates the spread of a hoax only at low forgetting rates, but has no effect when agents forget at faster rates. This finding may inform the development of mitigation techniques and overall inform on the risks of uncontrolled misinformation online.

Includes members:
  Member "how algorithmic popularity bias hinders or promotes quality":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on bias and fairness in machine learning")
  Member "limited individual attention and online virality of low quality information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "science vs conspiracy collective narratives in the age of misinformation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the covid 19 social media infodemic")
  Member "measuring online social bubbles":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "positive algorithmic bias cannot stop fragmentation in homophilic social networks")
  Member "computational fact checking from knowledge networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "knowledge graphs")
  Member "knowledge based trust estimating the trustworthiness of web sources":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "detecting toxicity in news articles application to bulgarian")
  Member "viral misinformation the role of homophily and polarization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "towards understanding the information ecosystem through the lens of multiple web communities")
  Member "the role of social networks in information diffusion":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deep learning approach on information diffusion in heterogeneous networks")

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)