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 "false news on social media a data driven survey"):
  Abstract: In the past few years, the research community has dedicated growing interest to the issue of false news circulating on social networks. The widespread attention on detecting and characterizing false news has been motivated by considerable backlashes of this threat against the real world. As a matter of fact, social media platforms exhibit peculiar characteristics, with respect to traditional news outlets, which have been particularly favorable to the proliferation of deceptive information. They also present unique challenges for all kind of potential interventions on the subject. As this issue becomes of global concern, it is also gaining more attention in academia. The aim of this survey is to offer a comprehensive study on the recent advances in terms of detection, characterization and mitigation of false news that propagate on social media, as well as the challenges and the open questions that await future research on the field. We use a data-driven approach, focusing on a classification of the features that are used in each study to characterize false information and on the datasets used for instructing classification methods. At the end of the survey, we highlight emerging approaches that look most promising for addressing false news.

Includes members:
  Member "the junk news aggregator examining junk news posted on facebook starting with the 2018 us midterm elections":
    also connected through other hyperedges:
      (none)
  Member "a retrospective analysis of the fake news challenge stance detection task":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "stance detection benchmark how robust is your stance detection")
  Member "the rise of guardians fact checking url recommendation to combat fake news":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "attributed multi relational attention network for fact checking url recommendation")
  Member "automated fact checking task formulations methods and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fact check worthiness detection as positive unlabelled learning")
  Member "fakenewsnet a data repository with news content social context and dynamic information for studying fake news on social media":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "discover your social identity from what you tweet a content based approach")
  Member "anatomy of an online misinformation network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mining social media data for biomedical signals and health related behavior")
  Member "declare debunking fake news and false claims using evidence aware deep learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mining disinformation and fake news concepts methods and recent advancements")
  Member "detection and resolution of rumours in social media a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "discover your social identity from what you tweet a content based approach")

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)